11g SQL Tuning Workshop - Volume 2

Volume II • Student Guide

D52163GC10 Edition 1.0 June 2008 D54948

Oracle Internal & Oracle Academy Use Only

Oracle Database 11g: SQL Tuning Workshop

Author

Copyright © 2008, Oracle. All rights reserved.

Jean-François Verrier

Disclaimer

Muriel Fry (Special thanks) Joel Goodman Harald van Breederode Jörn Bartels Pekka Siltala Bernard Soleillant James Spiller Clay Fuller Ira Singer Christopher Andrews Magnus Isaksson Sean Kim Trevor Bauwen Yash Jain

Editors Amitha Narayan Raj Kumar

Graphic Designer Priya Saxena

Publishers Jothi Lakshmi Veena Narasimhan

This document contains proprietary information and is protected by copyright and other intellectual property laws. You may copy and print this document solely for your own use in an Oracle training course. The document may not be modified or altered in any way. Except where your use constitutes "fair use" under copyright law, you may not use, share, download, upload, copy, print, display, perform, reproduce, publish, license, post, transmit, or distribute this document in whole or in part without the express authorization of Oracle. The information contained in this document is subject to change without notice. If you find any problems in the document, please report them in writing to: Oracle University, 500 Oracle Parkway, Redwood Shores, California 94065 USA. This document is not warranted to be error-free. Restricted Rights Notice If this documentation is delivered to the United States Government or anyone using the documentation on behalf of the United States Government, the following notice is applicable: U.S. GOVERNMENT RIGHTS The U.S. Government’s rights to use, modify, reproduce, release, perform, display, or disclose these training materials are restricted by the terms of the applicable Oracle license agreement and/or the applicable U.S. Government contract. Trademark Notice Oracle is a registered trademark of Oracle Corporation and/or its affiliates. Other names may be trademarks of their respective owners.


Technical Contributors and Reviewers

1

Exploring the Oracle Database Architecture Objectives 1-2 Oracle Database Server Architecture: Overview 1-3 Connecting to the Database Instance 1-4 Oracle Database Memory Structures: Overview 1-6 Database Buffer Cache 1-7 Redo Log Buffer 1-8 Shared Pool 1-9 Processing a DML Statement: Example 1-10 COMMIT Processing: Example 1-11 Large Pool 1-12 Java Pool and Streams Pool 1-13 Program Global Area (PGA) 1-14 Background Process Roles 1-15 Automatic Shared Memory Management 1-16 Automated SQL Execution Memory Management 1-17 Automatic Memory Management 1-18 Database Storage Architecture 1-19 Logical and Physical Database Structures 1-21 Segments, Extents, and Blocks 1-23 SYSTEM and SYSAUX Tablespaces 1-24 Summary 1-25 Practice 1: Overview 1-26

2

Introduction to SQL Tuning Objectives 2-2 Reasons for Inefficient SQL Performance 2-3 Inefficient SQL: Examples 2-4 Performance Monitoring Solutions 2-6 Monitoring and Tuning Tools: Overview 2-8 EM Performance Pages for Reactive Tuning 2-9 Tuning Tools: Overview 2-10 SQL Tuning Tasks: Overview 2-11 CPU and Wait Time Tuning Dimensions 2-12 Scalability with Application Design, Implementation, and Configuration 2-13 iii


Contents

3

Introduction to the Optimizer Objectives 3-2 Structured Query Language 3-3 SQL Statement Representation 3-4 SQL Statement Implementation 3-5 SQL Statement Processing: Overview 3-6 SQL Statement Processing: Steps 3-7 Step 1: Create a Cursor 3-8 Step 2: Parse the Statement 3-9 Steps 3 and 4: Describe and Define 3-10 Steps 5 and 6: Bind and Parallelize 3-11 Steps 7 Through 9 3-12 SQL Statement Processing PL/SQL: Example 3-13 SQL Statement Parsing: Overview 3-14 Why Do You Need an Optimizer? 3-16 Optimization During Hard Parse Operation 3-18 Transformer: OR Expansion Example 3-19 Transformer: Subquery Unnesting Example 3-20 Transformer: View Merging Example 3-21 Transformer: Predicate Pushing Example 3-22 Transformer: Transitivity Example 3-23 Cost-Based Optimizer 3-24 Estimator: Selectivity 3-25 Estimator: Cardinality 3-26 Estimator: Cost 3-27 Plan Generator 3-28 Controlling the Behavior of the Optimizer 3-29 Optimizer Features and Oracle Database Releases 3-34 iv


Common Mistakes on Customer Systems 2-14 Proactive Tuning Methodology 2-16 Simplicity in Application Design 2-17 Data Modeling 2-18 Table Design 2-19 Index Design 2-20 Using Views 2-21 SQL Execution Efficiency 2-22 Writing SQL to Share Cursors 2-24 Performance Checklist 2-25 Summary 2-26 Practice 2: Overview 2-27

4

Optimizer Operators Objectives 4-2 Row Source Operations 4-3 Main Structures and Access Paths 4-4 Full Table Scan 4-5 Full Table Scans: Use Cases 4-6 ROWID Scan 4-7 Sample Table Scans 4-8 Indexes: Overview 4-10 Normal B*-tree Indexes 4-12 Index Scans 4-13 Index Unique Scan 4-14 Index Range Scan 4-15 Index Range Scan: Descending 4-16 Descending Index Range Scan 4-17 Index Range Scan: Function-Based 4-18 Index Full Scan 4-19 Index Fast Full Scan 4-20 Index Skip Scan 4-21 Index Skip Scan: Example 4-23 Index Join Scan 4-24 The AND-EQUAL Operation 4-25 B*-tree Indexes and Nulls 4-26 Using Indexes: Considering Nullable Columns 4-27 Index-Organized Tables 4-28 Index-Organized Table Scans 4-29 Bitmap Indexes 4-30 Bitmap Index Access: Examples 4-31 Combining Bitmap Indexes: Examples 4-32 Combining Bitmap Index Access Paths 4-33 Bitmap Operations 4-34 Bitmap Join Index 4-35 Composite Indexes 4-36 Invisible Index: Overview 4-37 Invisible Indexes: Examples 4-38 Guidelines for Managing Indexes 4-39 Investigating Index Usage 4-41 Practice 4: Overview 4-43 v


Summary 3-35 Practice 3: Overview 3-36

5

Interpreting Execution Plans Objectives 5-2 What Is an Execution Plan? 5-3 Where to Find Execution Plans? 5-4 Viewing Execution Plans 5-6 The EXPLAIN PLAN Command 5-7 The EXPLAIN PLAN Command: Example 5-9 PLAN_TABLE 5-10 Displaying from PLAN_TABLE: Typical 5-11 Displaying from PLAN_TABLE: ALL 5-12 Displaying from PLAN_TABLE: ADVANCED 5-14

vi


Clusters 4-44 When Are Clusters Useful? 4-45 Cluster Access Path: Examples 4-47 Sorting Operators 4-48 Buffer Sort Operator 4-49 Inlist Iterator 4-50 View Operator 4-51 Count Stop Key Operator 4-52 Min/Max and First Row Operators 4-53 Join Methods 4-54 Nested Loops Join 4-55 Nested Loops Join: Prefetching 4-56 Nested Loops Join: 11g Implementation 4-57 Sort Merge Join 4-58 Hash Join 4-59 Cartesian Join 4-60 Join Types 4-61 Equijoins and Nonequijoins 4-62 Outer Joins 4-63 Semijoins 4-64 Antijoins 4-65 Other N-Array Operations 4-66 Filter Operations 4-67 Concatenation Operation 4-68 UNION [ALL], INTERSECT, MINUS 4-69 Result Cache Operator 4-70 Summary 4-71 Practice 4: Overview 4-72

AUTOTRACE 5-15 The AUTOTRACE Syntax 5-16 AUTOTRACE: Examples 5-17 AUTOTRACE: Statistics 5-18 Using the V$SQL_PLAN View 5-20 The V$SQL_PLAN_STATISTICS View 5-22 Links Between Important Dynamic Performance Views 5-23 Querying V$SQL_PLAN 5-25 Automatic Workload Repository (AWR) 5-27 Managing AWR with PL/SQL 5-29 Important AWR Views 5-31 Querying the AWR 5-32 Generating SQL Reports from AWR Data 5-34 SQL Monitoring: Overview 5-35 SQL Monitoring Report: Example 5-37 Interpreting an Execution Plan 5-40 Execution Plan Interpretation: Example 1 5-42 Execution Plan Interpretation: Example 2 5-45 Execution Plan Interpretation: Example 3 5-47 Reading More Complex Execution Plans 5-48 Reviewing the Execution Plan 5-49 Looking Beyond Execution Plans 5-50 Summary 5-51 Practice 5: Overview 5-52 6

Case Study: Star Transformation Objectives 6-2 The Star Schema Model 6-3 The Snowflake Schema Model 6-4 Star Query: Example 6-5 Execution Plan Without Star Transformation 6-6 Star Transformation 6-7 Star Transformation: Considerations 6-8 Star Transformation: Rewrite Example 6-9 Retrieving Fact Rows from One Dimension 6-10 Retrieving Fact Rows from All Dimensions 6-11 Joining the Intermediate Result Set with Dimensions 6-12 Star Transformation Plan: Example 1 6-13 Star Transformation: Further Optimization 6-14

vii


The V$SQL_PLAN Columns 5-21

7

Optimizer Statistics Objectives 7-2 Optimizer Statistics 7-3 Types of Optimizer Statistics 7-4 Table Statistics (DBA_TAB_STATISTICS) 7-5 Index Statistics (DBA_IND_STATISTICS) 7-6 Index Clustering Factor 7-8 Column Statistics (DBA_TAB_COL_STATISTICS) 7-10 Histograms 7-11 Frequency Histograms 7-12 Viewing Frequency Histograms 7-13 Height-Balanced Histograms 7-14 Viewing Height-Balanced Histograms 7-15 Histogram Considerations 7-16 Multicolumn Statistics: Overview 7-17 Expression Statistics: Overview 7-19 Gathering System Statistics 7-20 Gathering System Statistics: Example 7-22 Mechanisms for Gathering Statistics 7-24 Statistic Preferences: Overview 7-25 When to Gather Statistics Manually 7-27 Manual Statistics Gathering 7-28 Manual Statistics Collection: Factors 7-29 Managing Statistics Collection: Example 7-30 Optimizer Dynamic Sampling: Overview 7-31 Optimizer Dynamic Sampling at Work 7-32 OPTIMIZER_DYNAMIC_SAMPLING 7-33 Locking Statistics 7-34 Summary 7-35 Practice 7: Overview 7-36

viii


Using Bitmap Join Indexes 6-15 Star Transformation Plan: Example 2 6-16 Star Transformation Hints 6-17 Bitmap Join Indexes: Join Model 1 6-18 Bitmap Join Indexes: Join Model 2 6-19 Bitmap Join Indexes: Join Model 3 6-20 Bitmap Join Indexes: Join Model 4 6-21 Summary 6-22 Practice 6: Overview 6-23

Using Bind Variables Objectives 8-2 Cursor Sharing and Different Literal Values 8-3 Cursor Sharing and Bind Variables 8-4 Bind Variables in SQL*Plus 8-5 Bind Variables in Enterprise Manager 8-6 Bind Variable Peeking 8-7 Cursor Sharing Enhancements 8-9 The CURSOR_SHARING Parameter 8-11 Forcing Cursor Sharing: Example 8-12 Adaptive Cursor Sharing: Overview 8-13 Adaptive Cursor Sharing: Architecture 8-14 Adaptive Cursor Sharing: Views 8-16 Adaptive Cursor Sharing: Example 8-18 Interacting with Adaptive Cursor Sharing 8-19 Summary 8-20 Practice 8: Overview 8-21

9

Using Optimizer Hints Objectives 9-2 Optimizer Hints: Overview 9-3 Types of Hints 9-4 Specifying Hints 9-5 Rules for Hints 9-6 Hint Recommendations 9-7 Optimizer Hint Syntax: Example 9-8 Hint Categories 9-9 Optimization Goals and Approaches 9-10 Hints for Access Paths 9-11 The INDEX_COMBINE Hint: Example 9-15 Hints for Query Transformation 9-17 Hints for Join Orders 9-20 Hints for Join Operations 9-21 Additional Hints 9-23 Hints and Views 9-26 Global Table Hints 9-28 Specifying a Query Block in a Hint 9-29 Specifying a Full Set of Hints 9-30 Summary 9-31 Practice 9: Overview 9-32

ix


8

Invoking the trcsess Utility 10-15 The trcsess Utility: Example 10-16 SQL Trace File Contents 10-17 SQL Trace File Contents: Example 10-18 Formatting SQL Trace Files: Overview 10-19 Invoking the tkprof Utility 10-20 tkprof Sorting Options 10-22 Output of the tkprof Command 10-24 tkprof Output with No Index: Example 10-29 tkprof Output with Index: Example 10-30 Summary 10-31 Practice 10: Overview 10-32 11 Automating SQL Tuning Objectives 11-2 Tuning SQL Statements Automatically 11-3 Application Tuning Challenges 11-4 SQL Tuning Advisor: Overview 11-5 Stale or Missing Object Statistics 11-6 SQL Statement Profiling 11-7 Plan Tuning Flow and SQL Profile Creation 11-8 SQL Tuning Loop 11-9 Access Path Analysis 11-10 SQL Structure Analysis 11-11 SQL Tuning Advisor: Usage Model 11-12 Database Control and SQL Tuning Advisor 11-13 Running SQL Tuning Advisor: Example 11-14

x


10 Application Tracing Objectives 10-2 End-to-End Application Tracing Challenge 10-3 End-to-End Application Tracing 10-4 Location for Diagnostic Traces 10-5 What Is a Service? 10-6 Use Services with Client Applications 10-7 Tracing Services 10-8 Use Enterprise Manager to Trace Services 10-10 Service Tracing: Example 10-11 Session Level Tracing: Example 10-12 Trace Your Own Session 10-13 The trcsess Utility 10-14

Appendix A: Practices and Solutions Index

xi


Implementing Recommendations 11-15 SQL Access Advisor: Overview 11-16 SQL Access Advisor: Usage Model 11-17 Possible Recommendations 11-18 SQL Access Advisor Session: Initial Options 11-19 SQL Access Advisor: Workload Source 11-21 SQL Access Advisor: Recommendation Options 11-22 SQL Access Advisor: Schedule and Review 11-23 SQL Access Advisor: Results 11-24 SQL Access Advisor: Results and Implementation 11-25 SQL Tuning Loop 11-26 Automatic SQL Tuning 11-27 Automatic Tuning Process 11-28 Automatic SQL Tuning Controls 11-30 Automatic SQL Tuning Task 11-31 Configuring Automatic SQL Tuning 11-32 Automatic SQL Tuning: Result Summary 11-33 Automatic SQL Tuning: Result Details 11-34 Automatic SQL Tuning Result Details: Drilldown 11-35 Automatic SQL Tuning Considerations 11-36 Summary 11-37 Practice 11: Overview 11-38

xii



Appendix A Practices and Solutions

Practices for Lesson 1 ......................................................................................................... 3 Practice 1-1: Exploring the Database Architecture......................................................... 4 Practices for Lesson 2 ....................................................................................................... 12 Practice 2-1: Avoiding Common Mistakes................................................................... 13 Practices for Lesson 3 ....................................................................................................... 32 Practice 3-1: Understanding Optimizer Decisions........................................................ 33 Practices for Lesson 4 ....................................................................................................... 57 Practice 4-1: Using Different Access Paths .................................................................. 58 Practice 4-2: Using the Result Cache.......................................................................... 121 Practices for Lesson 5 ..................................................................................................... 144 Practice 5-1: Extracting Execution Plans.................................................................... 145 Practices for Lesson 6 ..................................................................................................... 179 Practice 6-1: Star Schema Tuning............................................................................... 180 Practices for Lesson 7 ..................................................................................................... 196 Practice 7-1: Using System Statistics ......................................................................... 197 Practice 7-2: Automatic Statistics Gathering.............................................................. 212 Practices for Lesson 8 ..................................................................................................... 240 Practice 8-1: Understanding Adaptive Cusrsor Sharing ............................................. 241 Practice 8-2: Understanding CURSOR_SHARING................................................... 260 Practices for Lesson 9 ..................................................................................................... 273 Practice 9-1: Using Hints ............................................................................................ 274 Practices for Lesson 10 ................................................................................................... 318 Practice 10-1: Tracing Applications ........................................................................... 319 Practices for Lesson 11 ................................................................................................... 363 Practice 11-1: Proactively Tuning High-Load SQL Statements................................. 364 Practice 11-2: Using SQL Access Advisor................................................................. 385 Practice 11-3: Using Automatic SQL Tuning............................................................. 415

Oracle Database 11g: SQL Tuning Workshop A - 2


Table of Contents


Practices for Lesson 1


Practice 1-1: Exploring the Database Architecture Fill in the blanks with the correct answers: 1) The two main components of Oracle RDBMS are _________________________ and _______________________.

3) A session is a connection between the _______________ process and either the ______________ process or the ________________ process. 4) Name some components of the System Global Area (SGA). •

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5) List some background processes: •

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•

___________________________

6) The _______________________ process writes the dirty buffers to the data files. 7) The _______________________ process writes the redo logs to the log files. 8) Name some files associated with an Oracle database.



2) An instance consists of _____________________and _____________________ processes.

•

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9) Some of the logical storage structures of an Oracle database are: •

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____________________________

10) The ___________________ process copies the redo log files to an archive destination. 11) The _____________________ contains data and control information for a server or a background process. 12) The logical tablespace structure is associated with the physical ____________________ files on disk. 13) State whether the following statements are true or false. a) The SGA includes the Database buffer cache and the Redo log buffer. ____ b) Each server process and background process has its own Program Global Area (PGA). ____ c) User processes run the application or Oracle tool code. ____ d) Oracle Database processes include server processes and background processes. ____.



Practice 1-1: Exploring the Database Architecture (continued)

Practice 1-1: Exploring the Database Architecture (continued) 14) From a terminal session connected as the oracle user, execute the processes.sh script located in your $HOME/solutions/Database_Architecture directory. What does this script show you?

[oracle@edrsr33p1-orcl Database_Architecture]$ ./processes.sh oracle 9537 1 0 01:00 ? 00:00:00 ora_w000_orcl oracle 12132 22002 0 Mar26 pts/4 00:01:08 /u01/app/oracle/product/11.1.0/db_1/jdk/bin/java -server -Xmx256M XX:MaxPermSize=200m -XX:MinHeapFreeRatio=20 -XX:MaxHeapFreeRatio=40 -DORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 Doracle.home=/u01/app/oracle/product/11.1.0/db_1/oc4j Doracle.oc4j.localhome=/u01/app/oracle/product/11.1.0/db_1/edrsr33p1 .us.oracle.com_orcl/sysman DEMSTATE=/u01/app/oracle/product/11.1.0/db_1/edrsr33p1.us.oracle.com _orcl -Doracle.j2ee.dont.use.memory.archive=true Djava.protocol.handler.pkgs=HTTPClient Doracle.security.jazn.config=/u01/app/oracle/product/11.1.0/db_1/oc4 j/j2ee/OC4J_DBConsole_edrsr33p1.us.oracle.com_orcl/config/jazn.xml Djava.security.policy=/u01/app/oracle/product/11.1.0/db_1/oc4j/j2ee/ OC4J_DBConsole_edrsr33p1.us.oracle.com_orcl/config/java2.policy Djavax.net.ssl.KeyStore=/u01/app/oracle/product/11.1.0/db_1/sysman/c onfig/OCMTrustedCerts.txtDjava.security.properties=/u01/app/oracle/product/11.1.0/db_1/oc4j/j 2ee/home/config/jazn.security.props DEMDROOT=/u01/app/oracle/product/11.1.0/db_1/edrsr33p1.us.oracle.com _orcl -Dsysman.md5password=true Drepapi.oracle.home=/u01/app/oracle/product/11.1.0/db_1 Ddisable.checkForUpdate=true Doracle.sysman.ccr.ocmSDK.websvc.keystore=/u01/app/oracle/product/11 .1.0/db_1/jlib/emocmclnt.ks Dice.pilots.html4.ignoreNonGenericFonts=true Djava.awt.headless=true -jar /u01/app/oracle/product/11.1.0/db_1/oc4j/j2ee/home/oc4j.jar -config /u01/app/oracle/product/11.1.0/db_1/oc4j/j2ee/OC4J_DBConsole_edrsr33 p1.us.oracle.com_orcl/config/server.xml oracle 12225 1 0 Mar26 ? 00:00:00 ora_pmon_orcl oracle 12227 1 0 Mar26 ? 00:00:00 ora_vktm_orcl oracle 12231 1 0 Mar26 ? 00:00:00 ora_diag_orcl oracle 12233 1 0 Mar26 ? 00:00:00 ora_dbrm_orcl oracle 12235 1 0 Mar26 ? 00:00:00 ora_psp0_orcl oracle 12239 1 0 Mar26 ? 00:00:00 ora_dia0_orcl oracle 12241 1 0 Mar26 ? 00:00:00 ora_mman_orcl oracle 12243 1 0 Mar26 ? 00:00:21 ora_dbw0_orcl oracle 12245 1 0 Mar26 ? 00:00:48 ora_lgwr_orcl oracle 12247 1 0 Mar26 ? 00:00:01 ora_ckpt_orcl oracle 12249 1 0 Mar26 ? 00:00:04 ora_smon_orcl oracle 12251 1 0 Mar26 ? 00:00:00 ora_reco_orcl oracle 12253 1 0 Mar26 ? 00:00:05 ora_mmon_orcl oracle 12255 1 0 Mar26 ? 00:00:01 ora_mmnl_orcl oracle 12257 1 0 Mar26 ? 00:00:00 ora_d000_orcl oracle 12259 1 0 Mar26 ? 00:00:00 ora_s000_orcl oracle 12282 1 0 Mar26 ? 00:00:00 ora_fbda_orcl



a) It shows you all the database instance processes currently running on your machine. This includes both background processes and foreground processes.

oracle 12284 1 0 Mar26 ? 00:00:00 ora_smco_orcl oracle 12290 1 0 Mar26 ? 00:00:00 ora_qmnc_orcl oracle 12302 1 0 Mar26 ? 00:00:03 oracleorcl (LOCAL=NO) oracle 12325 1 0 Mar26 ? 00:00:00 ora_q000_orcl oracle 12329 1 0 Mar26 ? 00:01:59 oracleorcl (LOCAL=NO) oracle 12331 1 0 Mar26 ? 00:00:12 oracleorcl (LOCAL=NO) oracle 12333 1 0 Mar26 ? 00:00:05 oracleorcl (LOCAL=NO) oracle 12335 1 0 Mar26 ? 00:00:37 oracleorcl (LOCAL=NO) oracle 12340 1 0 Mar26 ? 00:01:51 oracleorcl (LOCAL=NO) oracle 12346 1 0 Mar26 ? 00:00:01 oracleorcl (LOCAL=NO) oracle 12362 1 0 Mar26 ? 00:00:00 ora_q001_orcl oracle 12570 1 0 Mar26 ? 00:00:01 ora_cjq0_orcl oracle 20119 1 0 14:50 ? 00:00:00 oracleorcl (LOCAL=NO) oracle 20482 20480 0 14:56 pts/2 00:00:00 grep orcl oracle 22002 1 0 Mar26 pts/4 00:00:08 /u01/app/oracle/product/11.1.0/db_1/perl/bin/perl /u01/app/oracle/product/11.1.0/db_1/bin/emwd.pl dbconsole /u01/app/oracle/product/11.1.0/db_1/edrsr33p1.us.oracle.com_orcl/sys man/log/emdb.nohup [oracle@edrsr33p1-orcl Database_Architecture]$ -------------------------------------------------------------#!/bin/bash ps -ef | grep orcl

15) From a terminal session connected as the oracle user, execute the files.sh script located in your $HOME/solutions/Database_Architecture directory. What does this script show you? a) This script shows you the location and names of all database files, the initialization file, the password file, and trace files. [oracle@edrsr33p1-orcl Database_Architecture]$ ./files.sh SQL*Plus: Release 11.1.0.6.0 - Production on Thu Mar 27 17:58:56 2008 Copyright (c) 1982, 2007, Oracle.

All rights reserved.

Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options



Practice 1-1: Exploring the Database Architecture (continued)

Practice 1-1: Exploring the Database Architecture (continued) SQL> SQL> col name format a45 SQL> SQL> select name from v$controlfile;

SQL> SQL> SQL> col member format a45 SQL> SQL> select group#,member from v$logfile; GROUP# ---------3 2 1

MEMBER --------------------------------------------/u01/app/oracle/oradata/orcl/redo03.log /u01/app/oracle/oradata/orcl/redo02.log /u01/app/oracle/oradata/orcl/redo01.log

SQL> SQL> SQL> col tablespace_name format a20 SQL> col file_name format a45 SQL> SQL> select tablespace_name, file_name from dba_data_files; TABLESPACE_NAME -------------------USERS UNDOTBS1 SYSAUX SYSTEM EXAMPLE

FILE_NAME --------------------------------------------/u01/app/oracle/oradata/orcl/users01.dbf /u01/app/oracle/oradata/orcl/undotbs01.dbf /u01/app/oracle/oradata/orcl/sysaux01.dbf /u01/app/oracle/oradata/orcl/system01.dbf /u01/app/oracle/oradata/orcl/example01.dbf

SQL> SQL> select tablespace_name, file_name from dba_temp_files; TABLESPACE_NAME FILE_NAME -------------------- --------------------------------------------TEMP /u01/app/oracle/oradata/orcl/temp01.dbf SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options -rw-rw---- 1 oracle oinstall 1544 Aug 22 2007 /u01/app/oracle/product/11.1.0/db_1/dbs/hc_orcl.dat -rw-r----- 1 oracle oinstall 1536 Mar 26 22:03 /u01/app/oracle/product/11.1.0/db_1/dbs/orapworcl -rw-r----- 1 oracle oinstall 2560 Mar 27 03:13 /u01/app/oracle/product/11.1.0/db_1/dbs/spfileorcl.ora



NAME --------------------------------------------/u01/app/oracle/oradata/orcl/control01.ctl /u01/app/oracle/oradata/orcl/control02.ctl /u01/app/oracle/oradata/orcl/control03.ctl

Practice 1-1: Exploring the Database Architecture (continued) alert cdump hm incident incpkg ir lck metadata stage trace -rw-r--r-- 1 oracle oinstall 557386 Mar 27 13:00 /u01/app/oracle/diag/rdbms/orcl/orcl/trace/alert_orcl.log [oracle@edrsr33p1-orcl Database_Architecture]$

sweep

-------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Database_Architecture export ORACLE_SID=orcl

export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin

sqlplus / as sysdba @files.sql ls -l $ORACLE_HOME/dbs/*orcl* ls /u01/app/oracle/diag/rdbms/orcl/orcl ls -l /u01/app/oracle/diag/rdbms/orcl/orcl/trace/alert* -------------------------------------------------------------set echo on col name format a45 select name from v$controlfile;

col member format a45 select group#,member from v$logfile;

col tablespace_name format a20 col file_name format a45 select tablespace_name, file_name from dba_data_files; select tablespace_name, file_name from dba_temp_files; exit;

16) From a terminal session connected as the oracle user, execute the sga.sh script located in your $HOME/solutions/Database_Architecture directory. What does this script show you?



export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1

Practice 1-1: Exploring the Database Architecture (continued) a) This script prints the various pools held in your SGA. [oracle@edrsr33p1-orcl Database_Architecture]$ ./sga.sh SQL*Plus: Release 11.1.0.6.0 - Production on Thu Mar 27 18:15:02 2008 Copyright (c) 1982, 2007, Oracle.


SQL> SQL> select * from v$sgainfo; NAME BYTES RES -------------------------------- ---------- --Fixed SGA Size 1303188 No Redo Buffers 5181440 No Buffer Cache Size 335544320 Yes Shared Pool Size 276824064 Yes Large Pool Size 4194304 Yes Java Pool Size 12582912 Yes Streams Pool Size 0 Yes Shared IO Pool Size 0 Yes Granule Size 4194304 No Maximum SGA Size 845348864 No Startup overhead in Shared Pool 46137344 No NAME BYTES RES -------------------------------- ---------- --Free SGA Memory Available 209715200 12 rows selected. SQL> SQL> col component format a30 SQL> SQL> select component,current_size,min_size,max_size from v$sga_dynamic_components; COMPONENT CURRENT_SIZE MIN_SIZE MAX_SIZE ------------------------------ ------------ ---------- ---------shared pool 276824064 226492416 276824064 large pool 4194304 4194304 4194304 java pool 12582912 12582912 12582912 streams pool 0 0 0 DEFAULT buffer cache 335544320 335544320 385875968 KEEP buffer cache 0 0 0 RECYCLE buffer cache 0 0 0 DEFAULT 2K buffer cache 0 0 0 DEFAULT 4K buffer cache 0 0 0 DEFAULT 8K buffer cache 0 0 0




Practice 1-1: Exploring the Database Architecture (continued) DEFAULT 16K buffer cache

0

0

0

COMPONENT CURRENT_SIZE MIN_SIZE MAX_SIZE ------------------------------ ------------ ---------- ---------DEFAULT 32K buffer cache 0 0 0 Shared IO Pool 0 0 0 ASM Buffer Cache 0 0 0

SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Database_Architecture]$

-------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Database_Architecture export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin

sqlplus / as sysdba @sga.sql -------------------------------------------------------------set echo on select * from v$sgainfo; col component format a30 select component,current_size,min_size,max_size from v$sga_dynamic_components; exit;



14 rows selected.




Practice 2-1: Avoiding Common Mistakes In this practice, you examine some common mistakes in writing SQL statements. You have to find a workaround to enhance performance. 1) You analyze a correlated subquery first. Before executing the culprit statement, execute the correlation_setup.sh script to set up the environment for this example. Make sure you run the script from a terminal session connected as the oracle user. You can find the scripts for all the following cases in your $HOME/solutions/Common_Mistakes directory. [oracle@edrsr33p1-orcl Common_Mistakes]$ ./correlation_setup.sh

Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> User altered. SQL> SQL> Grant succeeded. SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Common_Mistakes]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Common_Mistakes export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba <


SQL*Plus: Release 11.1.0.6.0 - Production on Wed Mar 26 20:21:50 2008

Practice 2-1: Avoiding Common Mistakes (continued) 2) Connected as the SH user from a SQL*Plus session (stay connected to that session until the end of this case), make sure you execute the following command: set timing on @flush The goal of the first command is to tell you how long the next command takes to execute. The flush.sql script flushes both the shared pool and the buffer cache to avoid most caching effects so that you can have good comparisons between two executions. Note: You should not use commands found in this script on a production system.

SQL*Plus: Release 11.1.0.6.0 - Production on Wed Mar 26 20:37:49 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> set timing on SQL> @flush System altered. Elapsed: 00:00:00.21 System altered. Elapsed: 00:00:00.49 SQL> -------------------------------------------------------------alter system flush shared_pool; alter system flush buffer_cache;

3) From the same SQL*Plus session, execute the following statement and note the time it takes to execute (You can use the correlation.sql script.): SELECT COUNT(*) FROM products p WHERE prod_list_price < 1.15 * (SELECT avg(unit_cost) FROM costs c WHERE c.prod_id = p.prod_id); SQL> SQL> SQL> 2 3

@correlation SELECT COUNT(*) FROM products p WHERE prod_list_price < 1.15 * (SELECT avg(unit_cost)



[oracle@edrsr33p1-orcl Common_Mistakes]$ sqlplus sh/sh

Practice 2-1: Avoiding Common Mistakes (continued) 4 5

FROM costs c WHERE c.prod_id = p.prod_id);

COUNT(*) ---------46 Elapsed: 00:00:01.21 SQL> --------------------------------------------------------------

SELECT COUNT(*) FROM products p WHERE prod_list_price < 1.15 * (SELECT avg(unit_cost) FROM costs c WHERE c.prod_id = p.prod_id);

4) Before trying to fix the previous statement, flush your environment again using the flush.sql script from the SQL*Plus session. SQL> @flush SQL> alter system flush shared_pool; System altered. Elapsed: 00:00:00.10 SQL> alter system flush buffer_cache; System altered. Elapsed: 00:00:00.17 SQL>

5) How do you rewrite this statement to enhance performance? Test your solution. You should discuss this with your instructor. SQL> @nocorrelation SQL> SQL> set timing on SQL> set echo on SQL> SQL> SELECT COUNT(*) 2 FROM products p, (SELECT prod_id, AVG(unit_cost) ac FROM costs GROUP BY prod_id) c 3 WHERE p.prod_id = c.prod_id AND 4 p.prod_list_price < 1.15 * c.ac; COUNT(*) ---------46 Elapsed: 00:00:00.16



set timing on set echo on

Practice 2-1: Avoiding Common Mistakes (continued) SQL> -------------------------------------------------------------set timing on set echo on SELECT COUNT(*) FROM products p, (SELECT prod_id, AVG(unit_cost) ac FROM costs GROUP BY prod_id) c WHERE p.prod_id = c.prod_id AND p.prod_list_price < 1.15 * c.ac;

SQL> exit Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Common_Mistakes]$

7) From your terminal session, execute the correlation_cleanup.sh script to clean up your environment. [oracle@edrsr33p1-orcl Common_Mistakes]$ ./correlation_cleanup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Wed Mar 26 20:49:22 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> Revoke succeeded. SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Common_Mistakes]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Common_Mistakes export ORACLE_SID=orcl



6) Exit from your SQL*Plus session.

Practice 2-1: Avoiding Common Mistakes (continued) export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba <
8) Before continuing, execute the setup_rest.sh script to set up the environment for all the examples that follow. Make sure you run the script from a terminal session connected as the oracle user. You can find the scripts for all the following cases in your $HOME/solutions/Common_Mistakes directory. [oracle@edrsr33p1-orcl Common_Mistakes]$ ./setup_rest.sh SQL*Plus: Release 11.1.0.6.0 - Production on Wed Mar 26 20:59:53 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> SQL> SQL> drop user jfv cascade * ERROR at line 1: ORA-01918: user 'JFV' does not exist

SQL> SQL> User created. SQL> SQL> Grant succeeded. SQL> SQL> Connected. SQL> SQL> drop table orders purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> SQL> Table created. SQL> SQL> 2 3 4 5 6 7 PL/SQL procedure successfully completed.



EOF

Practice 2-1: Avoiding Common Mistakes (continued) SQL> SQL> 2 3 4 5 6 7 PL/SQL procedure successfully completed. SQL> SQL> drop table employees purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> SQL> Table created. SQL> SQL> 2 3 4 5 6 7 PL/SQL procedure successfully completed. SQL> SQL> Table created. SQL> SQL> 2 3 4 5 6 7 PL/SQL procedure successfully completed. SQL> SQL> Index created. SQL> SQL> SQL> drop table old purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> drop table new purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> SQL> Table created. SQL> Table created. SQL> SQL> 2 3 4 5 6 7 PL/SQL procedure successfully completed. SQL> SQL> 2 3 4 5 6 7 PL/SQL procedure successfully completed. SQL> SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production



SQL> drop table job_history purge * ERROR at line 1: ORA-00942: table or view does not exist

Practice 2-1: Avoiding Common Mistakes (continued) With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Common_Mistakes]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Common_Mistakes export ORACLE_SID=orcl

export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba <



Practice 2-1: Avoiding Common Mistakes (continued) end; / drop table employees purge; drop table job_history purge;

begin for i in 1..500000 loop insert into employees values(i,'aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaa'); end loop; commit; end; / create table job_history (employee_id number, job varchar2(500)); begin for i in 1..500000 loop insert into job_history values(mod(i,1000),'aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaa'); end loop; commit; end; / create index job_history_empid_indx on job_history(employee_id);

drop table old purge; drop table new purge; create table old(name varchar2(10), other varchar2(500)); create table new(name varchar2(10), other varchar2(500)); begin for i in 1..500000 loop insert into old values(i,'aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaa'); end loop; commit; end; / begin



create table employees (employee_id number primary key, name varchar2(500));

Practice 2-1: Avoiding Common Mistakes (continued) for i in 1..500000 loop insert into new values(500000+i,'aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaa'); end loop; commit; end; /

9) Connect as the JFV user from a SQL*Plus session and stay connected in that session until further notice. In the session, set SQL*Plus timings on and flush your environment again before starting the second case. You can use the set timing on command and the flush.sql script for this. [oracle@edrsr33p1-orcl Common_Mistakes]$ sqlplus jfv/jfv SQL*Plus: Release 11.1.0.6.0 - Production on Wed Mar 26 21:06:33 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> set timing on SQL> @flush System altered. Elapsed: 00:00:00.33 System altered. Elapsed: 00:00:07.12 SQL> -------------------------------------------------------------alter system flush shared_pool; alter system flush buffer_cache;



EOF

Practice 2-1: Avoiding Common Mistakes (continued) 10) The second case you analyze is a join case. From your SQL*Plus session, execute the following query and note the time it takes to complete: SELECT count(*) FROM job_history jh, employees e WHERE substr(to_char(e.employee_id),1)=substr(to_char(jh.employee_id),1);

COUNT(*) ---------499500 Elapsed: 00:00:03.03 SQL> -------------------------------------------------------------set timing on set echo on SELECT count(*) FROM job_history jh, employees e WHERE substr(to_char(e.employee_id),1) = substr(to_char(jh.employee_id),1);

11) Before trying to fix the previous statement, flush your environment again using the flush.sql script from your SQL*Plus session. SQL> @flush SQL> alter system flush shared_pool; System altered. Elapsed: 00:00:00.12 SQL> alter system flush buffer_cache; System altered. Elapsed: 00:00:00.72 SQL> -------------------------------------------------------------alter system flush shared_pool; alter system flush buffer_cache;

12) How would you rewrite the previous query for better performance? Test your solution. You should discuss this with your instructor.



SQL> @join SQL> SQL> SELECT count(*) 2 FROM job_history jh, employees e 3 WHERE substr(to_char(e.employee_id),1) = substr(to_char(jh.employee_id),1);

Practice 2-1: Avoiding Common Mistakes (continued) SQL> SQL> SQL> SQL> SQL> SQL> 2 3

@better_join set timing on set echo on SELECT count(*) FROM job_history jh, employees e WHERE e.employee_id = jh.employee_id;

COUNT(*) ---------499500

-------------------------------------------------------------set timing on set echo on SELECT count(*) FROM job_history jh, employees e WHERE e.employee_id = jh.employee_id;

13) Before analyzing the third case, flush your environment again using the flush.sql script from your SQL*Plus session. SQL> @flush SQL> alter system flush shared_pool; System altered. Elapsed: 00:00:00.11 SQL> alter system flush buffer_cache; System altered. Elapsed: 00:00:00.23 SQL> -------------------------------------------------------------alter system flush shared_pool; alter system flush buffer_cache;

14) The third case you analyze is a simple predicate case. Still connected as the JFV user from your SQL*Plus session, execute the following query and note the time it takes to complete: SELECT * FROM orders WHERE order_id_char = 1205; SQL> @simple_predicate SQL> SQL> set timing on SQL> set echo on



Elapsed: 00:00:00.70 SQL>

Practice 2-1: Avoiding Common Mistakes (continued) SQL> SQL> SELECT * FROM orders WHERE order_id_char = 1205;

Elapsed: 00:00:07.62 SQL> -------------------------------------------------------------set timing on set echo on SELECT * FROM orders WHERE order_id_char = 1205;

15) Before trying to fix the SELECT statement in step 14, flush your environment again using the flush.sql script. SQL> @flush SQL> alter system flush shared_pool; System altered. Elapsed: 00:00:00.13 SQL> alter system flush buffer_cache; System altered. Elapsed: 00:00:00.20 SQL>

16) How would you rewrite the previous statement for better performance? Test your solution. You should discuss this with your instructor. SQL> SQL> SQL> SQL> SQL> SQL>

@better_predicate set timing on set echo on SELECT * FROM orders WHERE order_id_char = '1205';

ORDER_ID_CHAR ORDER_TOTAL -------------------------------------------------- ----------CUSTOMER_NAME



ORDER_ID_CHAR ORDER_TOTAL -------------------------------------------------- ----------CUSTOMER_NAME ------------------------------------------------------------------------------1205 100 aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa

Practice 2-1: Avoiding Common Mistakes (continued) ------------------------------------------------------------------------------1205 100 aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa


set timing on set echo on SELECT * FROM orders WHERE order_id_char = '1205';

17) Before proceeding with the next analysis, flush your environment again using the flush.sql script. SQL> @flush SQL> alter system flush shared_pool; System altered. Elapsed: 00:00:00.11 SQL> alter system flush buffer_cache; System altered. Elapsed: 00:00:00.11 SQL> -------------------------------------------------------------alter system flush shared_pool; alter system flush buffer_cache;

18) The fourth case is a UNION case. Execute the following query and note the time it takes to complete: select count(*) from (select name from old union select name from new); SQL> SQL> SQL> SQL> SQL> SQL> 2

@union set timing on set echo on select count(*) from (select name from old union select name from new);

COUNT(*)



--------------------------------------------------------------

Practice 2-1: Avoiding Common Mistakes (continued) ---------1000000 Elapsed: 00:00:06.39 SQL>

19) Before investigating a better solution, flush your environment again using the flush.sql script. SQL> @flush SQL> alter system flush shared_pool;

Elapsed: 00:00:00.10 SQL> alter system flush buffer_cache; System altered. Elapsed: 00:00:00.09 SQL>

20) How would you rewrite the previous statement for better performance? Test your solution. You should discuss this with your instructor. SQL> SQL> SQL> SQL> SQL> SQL> 2

@better_union set timing on set echo on select count(*) from (select name from old union all select name from new);

COUNT(*) ---------1000000 Elapsed: 00:00:00.42 SQL>

21) Execute the multiple_setup.sql script to set up the environment for this case. SQL> @multiple_setup SQL> create table myemp as select * from hr.employees; Table created. SQL> insert into myemp select * from myemp; / / / / / / / / / /



System altered.

Practice 2-1: Avoiding Common Mistakes (continued) / / / / / commit; 107 rows created. SQL> 214 rows created.

SQL> 856 rows created. SQL> 1712 rows created. SQL> 3424 rows created. SQL> 6848 rows created. SQL> 13696 rows created. SQL> 27392 rows created. SQL> 54784 rows created. SQL> 109568 rows created. SQL> 219136 rows created. SQL> 438272 rows created. SQL> 876544 rows created. SQL> 1753088 rows created. SQL> 3506176 rows created. SQL> Commit complete.



SQL> 428 rows created.

Practice 2-1: Avoiding Common Mistakes (continued) SQL> insert into myemp select * from myemp; commit; 7012352 rows created. SQL> Commit complete. SQL>

SQL> @multiple1 SQL> set timing on SQL> SQL> SQL> SELECT COUNT (*) FROM myemp WHERE salary < 2000; 2 3

COUNT(*) ---------0 Elapsed: 00:00:15.49 SQL> SELECT COUNT (*) FROM myemp WHERE salary BETWEEN 2000 AND 4000; 2 3 COUNT(*) ---------5636096 Elapsed: 00:00:17.14 SQL> SELECT COUNT (*) FROM myemp WHERE salary>4000; 2 3 COUNT(*) ---------8388608 Elapsed: 00:00:18.12 SQL>

23) How would you rewrite the statements found in multiple1.sql script for better performance? SQL> @multiple2 SQL> SELECT COUNT (CASE WHEN salary < 2000 2 THEN 1 ELSE null END) count1,



22) Execute the multiple1.sql script and note the total time it takes to execute.

Practice 2-1: Avoiding Common Mistakes (continued) 3 4 5 6 7

COUNT (CASE WHEN THEN COUNT (CASE WHEN THEN FROM myemp;

salary 1 ELSE salary 1 ELSE

BETWEEN 2001 AND 4000 null END) count2, > 4000 null END) count3

COUNT1 COUNT2 COUNT3 ---------- ---------- ---------0 5636096 8388608 Elapsed: 00:00:18.19 SQL>

SQL> exit Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Common_Mistakes]$

25) You now analyze a fifth case that deals with database connections. Execute the bad_connect.sh script from your terminal window connected as the oracle user. Note the time it takes to complete. [oracle@edrsr33p1-orcl Common_Mistakes]$ ./bad_connect.sh Wed Mar 26 21:56:42 GMT-7 2008 Wed Mar 26 21:57:07 GMT-7 2008 [oracle@edrsr33p1-orcl Common_Mistakes]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Common_Mistakes export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin

STREAM_NUM=0 MAX_STREAM=500 date while [ $STREAM_NUM -lt $MAX_STREAM ]; do # one more let STREAM_NUM="STREAM_NUM+1" # start one more stream




Practice 2-1: Avoiding Common Mistakes (continued) sqlplus -s jfv/jfv @select.sql >> /tmp/bad_connect.log 2>&1 done date --------------------------------------------------------------

26) Analyze the bad_connect.sh script and try to find a better solution to enhance the performance of that application. Test your solution. You should discuss this with your instructor. [oracle@edrsr33p1-orcl Common_Mistakes]$ ./better_connect.sh Wed Mar 26 22:00:48 GMT-7 2008 Wed Mar 26 22:00:50 GMT-7 2008 [oracle@edrsr33p1-orcl Common_Mistakes]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Common_Mistakes export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin

date sqlplus -s jfv/jfv @select2.sql >> /tmp/better_connect.log 2>&1 date -------------------------------------------------------------declare c number; begin for i in 1..500 loop select count(*) into c from dba_users; end loop; end; / exit;



select count(*) from dba_users; exit;

Practice 2-1: Avoiding Common Mistakes (continued) 27) Clean up your environment by executing the cleanup_rest.sh script from your terminal session. [oracle@edrsr33p1-orcl Common_Mistakes]$ ./cleanup_rest.sh SQL*Plus: Release 11.1.0.6.0 - Production on Wed Mar 26 22:03:10 2008 All rights reserved.

Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> SQL> SQL> User dropped. SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Common_Mistakes]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Common_Mistakes export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba <






Practice 3-1: Understanding Optimizer Decisions In this practice, you try to understand optimizer decisions relating to which execution plan to use. All the scripts needed for this practice can be found in your $HOME/solutions/Trace_Event directory.

SELECT ch.channel_class, c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold) sales_amount FROM sh.sales s,sh.times t,sh.customers c,sh.channels ch WHERE s.time_id = t.time_id AND s.cust_id = c.cust_id AND s.channel_id = ch.channel_id AND c.cust_state_province = 'CA' AND ch.channel_desc IN ('Internet','Catalog') AND t.calendar_quarter_desc IN ('1999-Q1','1999-Q2') GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc; [oracle@edrsr33p1-orcl Trace_Event]$ ./te_setup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Wed Apr 9 22:16:53 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> alter system flush shared_pool; System altered. SQL> SQL> alter user sh identified by sh account unlock; User altered. SQL> SQL> connect sh/sh Connected. SQL> SQL> ALTER SESSION SET TRACEFILE_IDENTIFIER = 'MYOPTIMIZER'; Session altered. SQL> SQL> alter session set events '10053 trace name context forever, level 1'; Session altered. SQL>



1) Execute the te_setup.sh script. This script executes the following query and generates a trace file that contains all optimizer decisions.

Practice 3-1: Understanding Optimizer Decisions (continued) SQL> SELECT ch.channel_class, c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold) sales_amount 2 FROM sh.sales s,sh.times t,sh.customers c,sh.channels ch 3 WHERE s.time_id = t.time_id AND 4 s.cust_id = c.cust_id AND 5 s.channel_id = ch.channel_id AND 6 c.cust_state_province = 'CA' AND 7 ch.channel_desc IN ('Internet','Catalog') AND 8 t.calendar_quarter_desc IN ('1999-Q1','1999-Q2') 9 GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc;

SQL> SQL> exit Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options orcl_ora_1801_MYOPTIMIZER.trc orcl_ora_1801_MYOPTIMIZER.trm [oracle@edrsr33p1-orcl Trace_Event]$

2) With the help of your instructor, see the generated trace and interpret the important parts of the trace file. Note: This lab is only for demonstration purposes. Do not use it on your production system unless explicitly asked by Oracle Support Services. a) The 10053 trace output is broken down into a number of sections that broadly reflect the stages that the optimizer goes through in evaluating a plan. These stages are as follows: query, parameters used by the optimizer, base statistical information, base table access cost, join order and method computations, recosting for special features, such as query transformations. [oracle@edrsr33p1-orcl Trace_Event]$ cat myoptimizer.trc Trace file /u01/app/oracle/diag/rdbms/orcl/orcl/trace/orcl_ora_32643_MYOPTIMIZE R.trc Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options ORACLE_HOME = /u01/app/oracle/product/11.1.0/db_1 System name: Linux Node name: edrsr33p1.us.oracle.com Release: 2.6.9-55.0.0.0.2.ELsmp Version: #1 SMP Wed May 2 14:59:56 PDT 2007 Machine: i686 Instance name: orcl Redo thread mounted by this instance: 1 Oracle process number: 18 Unix process pid: 32643, image: [email protected] (TNS V1-V3)



no rows selected

Practice 3-1: Understanding Optimizer Decisions (continued) 2008-04-09 21:46:51.950 SESSION ID:(134.35423) 2008-04-09 21:46:51.950 CLIENT ID:() 2008-04-09 21:46:51.950 SERVICE NAME:(SYS$USERS) 2008-04-09 21:46:51.950 MODULE NAME:(SQL*Plus) 2008-04-09 21:46:51.950 ACTION NAME:() 2008-04-09 21:46:51.950

Registered qb: SEL$1 0xb7e0905c (PARSER) --------------------QUERY BLOCK SIGNATURE --------------------signature (): qb_name=SEL$1 nbfros=4 flg=0 fro(0): flg=4 objn=72254 hint_alias="C"@"SEL$1" fro(1): flg=4 objn=72252 hint_alias="CH"@"SEL$1" fro(2): flg=4 objn=72192 hint_alias="S"@"SEL$1" fro(3): flg=4 objn=72250 hint_alias="T"@"SEL$1" SPM: statement not found in SMB DOP: Automatic degree of parallelism is disabled: Parameter. PM: Considering predicate move-around in query block SEL$1 (#0) ************************** Predicate Move-Around (PM) ************************** OPTIMIZER INFORMATION ****************************************** ----- Current SQL Statement for this session (sql_id=70fqjd9u1zk7c) ----SELECT ch.channel_class, c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold) sales_amount FROM sh.sales s,sh.times t,sh.customers c,sh.channels ch WHERE s.time_id = t.time_id AND s.cust_id = c.cust_id AND s.channel_id = ch.channel_id AND c.cust_state_province = 'CA' AND ch.channel_desc IN ('Internet','Catalog') AND t.calendar_quarter_desc IN ('1999-Q1','1999-Q2') GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc ******************************************* Legend The following abbreviations are used by optimizer trace. CBQT - cost-based query transformation JPPD - join predicate push-down OJPPD - old-style (non-cost-based) JPPD FPD - filter push-down PM - predicate move-around CVM - complex view merging SPJ - select-project-join SJC - set join conversion SU - subquery unnesting OBYE - order by elimination ST - star transformation CNT - count(col) to count(*) transformation JE - Join Elimination qb - query block LB - leaf blocks DK - distinct keys



*** *** *** *** *** ***

LB/K - average number of leaf blocks per key DB/K - average number of data blocks per key CLUF - clustering factor NDV - number of distinct values Resp - response cost Card - cardinality Resc - resource cost NL - nested loops (join) SM - sort merge (join) HA - hash (join) CPUSPEED - CPU Speed IOTFRSPEED - I/O transfer speed IOSEEKTIM - I/O seek time SREADTIM - average single block read time MREADTIM - average multiblock read time MBRC - average multiblock read count MAXTHR - maximum I/O system throughput SLAVETHR - average slave I/O throughput dmeth - distribution method 1: no partitioning required 2: value partitioned 4: right is random (round-robin) 128: left is random (round-robin) 8: broadcast right and partition left 16: broadcast left and partition right 32: partition left using partitioning of right 64: partition right using partitioning of left 256: run the join in serial 0: invalid distribution method sel - selectivity ptn - partition *************************************** PARAMETERS USED BY THE OPTIMIZER ******************************** ************************************* PARAMETERS WITH ALTERED VALUES ****************************** Compilation Environment Dump _smm_min_size = 204 KB _smm_max_size = 40960 KB _smm_px_max_size = 102400 KB Bug Fix Control Environment

************************************* PARAMETERS WITH DEFAULT VALUES ****************************** Compilation Environment Dump optimizer_mode_hinted = false optimizer_features_hinted = 0.0.0 parallel_execution_enabled = true parallel_query_forced_dop = 0 parallel_dml_forced_dop = 0 parallel_ddl_forced_degree = 0 parallel_ddl_forced_instances = 0 _query_rewrite_fudge = 90 optimizer_features_enable = 11.1.0.6



Practice 3-1: Understanding Optimizer Decisions (continued)

Practice 3-1: Understanding Optimizer Decisions (continued) _optimizer_search_limit

= 5

optimizer_use_invisible_indexes = false flashback_data_archive_internal_cursor = 0 _optimizer_extended_stats_usage_control = 240 Bug Fix Control Environment fix 3834770 = 1 fix 3746511 = enabled fix 4519016 = enabled fix 3118776 = enabled fix 4488689 = enabled fix 2194204 = disabled … fix 6133948 = enabled fix 6239909 = enabled

*************************************** PARAMETERS IN OPT_PARAM HINT **************************** *************************************** Column Usage Monitoring is ON: tracking level = 1 ***************************************

Considering Query Transformations on query block SEL$1 (#0) ************************** Query transformations (QT) ************************** CBQT: Validity checks passed for 70fqjd9u1zk7c. CSE: Considering common sub-expression elimination in query block SEL$1 (#0) ************************* Common Subexpression elimination (CSE) ************************* CSE: CSE not performed on query block SEL$1 (#0). OBYE: Considering Order-by Elimination from view SEL$1 (#0) *************************** Order-by elimination (OBYE) *************************** OBYE: OBYE bypassed: no order by to eliminate. JE: Considering Join Elimination on query block SEL$1 (#0) ************************* Join Elimination (JE) ************************* SQL:******* UNPARSED QUERY IS ******* SELECT "CH"."CHANNEL_CLASS" "CHANNEL_CLASS","C"."CUST_CITY" "CUST_CITY","T"."CALENDAR_QUARTER_DESC" "CALENDAR_QUARTER_DESC",SUM("S"."AMOUNT_SOLD") "SALES_AMOUNT" FROM "SH"."SALES" "S","SH"."TIMES" "T","SH"."CUSTOMERS" "C","SH"."CHANNELS" "CH" WHERE "S"."TIME_ID"="T"."TIME_ID" AND "S"."CUST_ID"="C"."CUST_ID" AND "S"."CHANNEL_ID"="CH"."CHANNEL_ID" AND "C"."CUST_STATE_PROVINCE"='CA' AND ("CH"."CHANNEL_DESC"='Internet' OR "CH"."CHANNEL_DESC"='Catalog') AND ("T"."CALENDAR_QUARTER_DESC"='1999-Q1' OR



…

"T"."CALENDAR_QUARTER_DESC"='1999-Q2') GROUP BY "CH"."CHANNEL_CLASS","C"."CUST_CITY","T"."CALENDAR_QUARTER_DESC" Query block SEL$1 (#0) unchanged CNT: Considering count(col) to count(*) on query block SEL$1 (#0) ************************* Count(col) to Count(*) (CNT) ************************* CNT: COUNT() to COUNT(*) not done. JE: Considering Join Elimination on query block SEL$1 (#0) ************************* Join Elimination (JE) ************************* SQL:******* UNPARSED QUERY IS ******* SELECT "CH"."CHANNEL_CLASS" "CHANNEL_CLASS","C"."CUST_CITY" "CUST_CITY","T"."CALENDAR_QUARTER_DESC" "CALENDAR_QUARTER_DESC",SUM("S"."AMOUNT_SOLD") "SALES_AMOUNT" FROM "SH"."SALES" "S","SH"."TIMES" "T","SH"."CUSTOMERS" "C","SH"."CHANNELS" "CH" WHERE "S"."TIME_ID"="T"."TIME_ID" AND "S"."CUST_ID"="C"."CUST_ID" AND "S"."CHANNEL_ID"="CH"."CHANNEL_ID" AND "C"."CUST_STATE_PROVINCE"='CA' AND ("CH"."CHANNEL_DESC"='Internet' OR "CH"."CHANNEL_DESC"='Catalog') AND ("T"."CALENDAR_QUARTER_DESC"='1999-Q1' OR "T"."CALENDAR_QUARTER_DESC"='1999-Q2') GROUP BY "CH"."CHANNEL_CLASS","C"."CUST_CITY","T"."CALENDAR_QUARTER_DESC" Query block SEL$1 (#0) unchanged query block SEL$1 (#0) unchanged Considering Query Transformations on query block SEL$1 (#0) ************************** Query transformations (QT) ************************** CSE: Considering common sub-expression elimination in query block SEL$1 (#0) ************************* Common Subexpression elimination (CSE) ************************* CSE: CSE not performed on query block SEL$1 (#0). query block SEL$1 (#0) unchanged apadrv-start sqlid=8087006336042125548 : call(in-use=62016, alloc=81864), compile(in-use=64064, alloc=66868), execution(in-use=3376, alloc=4060) ******************************************* Peeked values of the binds in SQL statement ******************************************* CBQT: Considering cost-based transformation on query block SEL$1 (#0) ******************************** COST-BASED QUERY TRANSFORMATIONS ******************************** FPD: Considering simple filter push (pre rewrite) in query block SEL$1 (#0) FPD: Current where clause predicates "S"."TIME_ID"="T"."TIME_ID" AND "S"."CUST_ID"="C"."CUST_ID" AND "S"."CHANNEL_ID"="CH"."CHANNEL_ID" AND "C"."CUST_STATE_PROVINCE"='CA' AND ("CH"."CHANNEL_DESC"='Internet'





OBYE: Considering Order-by Elimination from view SEL$1 (#0) *************************** Order-by elimination (OBYE) *************************** OBYE: OBYE bypassed: no order by to eliminate. Considering Query Transformations on query block SEL$1 (#0) ************************** Query transformations (QT) ************************** CSE: Considering common sub-expression elimination in query block SEL$1 (#0) ************************* Common Subexpression elimination (CSE) ************************* CSE: CSE not performed on query block SEL$1 (#0). kkqctdrvTD-start on query block SEL$1 (#0) kkqctdrvTD-start: : call(in-use=62016, alloc=81864), compile(in-use=105980, alloc=109196), execution(in-use=3376, alloc=4060) kkqctdrvTD-cleanup: transform(in-use=0, alloc=0) : call(in-use=62016, alloc=81864), compile(in-use=106488, alloc=109196), execution(in-use=3376, alloc=4060) kkqctdrvTD-end: call(in-use=62016, alloc=81864), compile(in-use=106808, alloc=109196), execution(in-use=3376, alloc=4060) SJC: Considering set-join conversion in query block SEL$1 (#1) ************************* Set-Join Conversion (SJC) ************************* SJC: not performed CNT: Considering count(col) to count(*) on query block SEL$1 (#1) ************************* Count(col) to Count(*) (CNT) ************************* CNT: COUNT() to COUNT(*) not done. JE: Considering Join Elimination on query block SEL$1 (#1) ************************* Join Elimination (JE) ************************* SQL:******* UNPARSED QUERY IS ******* SELECT "CH"."CHANNEL_CLASS" "CHANNEL_CLASS","C"."CUST_CITY" "CUST_CITY","T"."CALENDAR_QUARTER_DESC" "CALENDAR_QUARTER_DESC",SUM("S"."AMOUNT_SOLD") "SALES_AMOUNT" FROM "SH"."SALES" "S","SH"."TIMES" "T","SH"."CUSTOMERS" "C","SH"."CHANNELS" "CH" WHERE "S"."TIME_ID"="T"."TIME_ID" AND "S"."CUST_ID"="C"."CUST_ID" AND "S"."CHANNEL_ID"="CH"."CHANNEL_ID" AND "C"."CUST_STATE_PROVINCE"='CA' AND ("CH"."CHANNEL_DESC"='Internet' OR "CH"."CHANNEL_DESC"='Catalog') AND ("T"."CALENDAR_QUARTER_DESC"='1999-Q1' OR "T"."CALENDAR_QUARTER_DESC"='1999-Q2') GROUP BY "CH"."CHANNEL_CLASS","C"."CUST_CITY","T"."CALENDAR_QUARTER_DESC"



OR "CH"."CHANNEL_DESC"='Catalog') AND ("T"."CALENDAR_QUARTER_DESC"='1999-Q1' OR "T"."C

Practice 3-1: Understanding Optimizer Decisions (continued) Query block SEL$1 (#1) unchanged PM: Considering predicate move-around in query block SEL$1 (#1) ************************** Predicate Move-Around (PM) ************************** PM: PM bypassed: Outer query contains no views. PM: PM bypassed: Outer query contains no views. kkqctdrvTD-start on query block SEL$1 (#1) kkqctdrvTD-start: : call(in-use=81660, alloc=98240), compile(in-use=109508, alloc=113320), execution(in-use=3376, alloc=4060)

kkqctdrvTD-end: call(in-use=81660, alloc=98240), compile(in-use=110304, alloc=113320), execution(in-use=3376, alloc=4060) kkqctdrvTD-start on query block SEL$1 (#1) kkqctdrvTD-start: : call(in-use=81660, alloc=98240), compile(in-use=110304, alloc=113320), execution(in-use=3376, alloc=4060) Registered qb: SEL$1 0xb7e01c6c (COPY SEL$1) --------------------QUERY BLOCK SIGNATURE --------------------signature(): NULL *********************************** Cost-Based Group By Placement *********************************** GBP: Checking validity of GBP for query block SEL$1 (#1) GBP: Checking validity of group-by placement for query block SEL$1 (#1) GBP: Bypassed: QB has disjunction. kkqctdrvTD-cleanup: transform(in-use=9008, alloc=9460) : call(in-use=81684, alloc=98240), compile(in-use=129100, alloc=132448), execution(in-use=3376, alloc=4060) kkqctdrvTD-end: call(in-use=81684, alloc=98240), compile(in-use=119884, alloc=132448), execution(in-use=3376, alloc=4060) GBP: Applying transformation directives GBP: Checking validity of group-by placement for query block SEL$1 (#1) GBP: Bypassed: QB has disjunction. JPPD: Considering Cost-based predicate pushdown from query block SEL$1 (#1) ************************************ Cost-based predicate pushdown (JPPD) ************************************ kkqctdrvTD-start on query block SEL$1 (#1) kkqctdrvTD-start: :



kkqctdrvTD-cleanup: transform(in-use=0, alloc=0) : call(in-use=81660, alloc=98240), compile(in-use=109984, alloc=113320), execution(in-use=3376, alloc=4060)

Practice 3-1: Understanding Optimizer Decisions (continued) call(in-use=81708, alloc=98240), compile(in-use=122632, alloc=132448), execution(in-use=3376, alloc=4060) kkqctdrvTD-cleanup: transform(in-use=0, alloc=0) : call(in-use=81708, alloc=98240), compile(in-use=123108, alloc=132448), execution(in-use=3376, alloc=4060)

JPPD: Applying transformation directives query block SEL$1 (#1) unchanged FPD: Considering simple filter push in query block SEL$1 (#1) "S"."TIME_ID"="T"."TIME_ID" AND "S"."CUST_ID"="C"."CUST_ID" AND "S"."CHANNEL_ID"="CH"."CHANNEL_ID" AND "C"."CUST_STATE_PROVINCE"='CA' AND ("CH"."CHANNEL_DESC"='Internet' OR "CH"."CHANNEL_DESC"='Catalog') AND ("T"."CALENDAR_QUARTER_DESC"='1999-Q1' OR "T"."C try to generate transitive predicate from check constraints for query block SEL$1 (#1) finally: "S"."TIME_ID"="T"."TIME_ID" AND "S"."CUST_ID"="C"."CUST_ID" AND "S"."CHANNEL_ID"="CH"."CHANNEL_ID" AND "C"."CUST_STATE_PROVINCE"='CA' AND ("CH"."CHANNEL_DESC"='Internet' OR "CH"."CHANNEL_DESC"='Catalog') AND ("T"."CALENDAR_QUARTER_DESC"='1999-Q1' OR "T"."C kkoqbc: optimizing query block SEL$1 (#1) : call(in-use=81716, alloc=98240), compile(in-use=124640, alloc=132448), execution(in-use=3376, alloc=4060) kkoqbc-subheap (create addr=0xb7d47960) **************** QUERY BLOCK TEXT **************** SELECT ch.channel_class, c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold) sales_amount FROM sh.sales s,sh.times t,sh.customers c,sh.channels ch WHERE s.time_id = t.time_id AND s.cust_id = c.cust_id AND s.channel_id = ch.channel_id --------------------QUERY BLOCK SIGNATURE --------------------signature (optimizer): qb_name=SEL$1 nbfros=4 flg=0 fro(0): flg=0 objn=72254 hint_alias="C"@"SEL$1" fro(1): flg=0 objn=72252 hint_alias="CH"@"SEL$1" fro(2): flg=0 objn=72192 hint_alias="S"@"SEL$1" fro(3): flg=0 objn=72250 hint_alias="T"@"SEL$1" ----------------------------SYSTEM STATISTICS INFORMATION ----------------------------Using NOWORKLOAD Stats CPUSPEED: 1263 millions instructions/sec



kkqctdrvTD-end: call(in-use=81708, alloc=98240), compile(in-use=123428, alloc=132448), execution(in-use=3376, alloc=4060)


*************************************** BASE STATISTICAL INFORMATION *********************** Table Stats:: Table: CHANNELS Alias: CH #Rows: 5 #Blks: 4 AvgRowLen: 40.00 Index Stats:: Index: CHANNELS_PK Col#: 1 LVLS: 0 #LB: 1 #DK: 5 LB/K: 1.00 DB/K: 1.00 CLUF: 1.00 *********************** Table Stats:: Table: CUSTOMERS Alias: C #Rows: 55500 #Blks: 1486 AvgRowLen: 180.00 Index Stats:: Index: CUSTOMERS_GENDER_BIX Col#: 4 LVLS: 1 #LB: 3 #DK: 2 LB/K: 1.00 DB/K: 2.00 CLUF: 5.00 Index: CUSTOMERS_MARITAL_BIX Col#: 6 LVLS: 1 #LB: 5 #DK: 11 LB/K: 1.00 DB/K: 1.00 CLUF: 18.00 Index: CUSTOMERS_PK Col#: 1 LVLS: 1 #LB: 115 #DK: 55500 LB/K: 1.00 DB/K: 1.00 CLUF: 54405.00 Index: CUSTOMERS_YOB_BIX Col#: 5 LVLS: 1 #LB: 19 #DK: 75 LB/K: 1.00 DB/K: 1.00 CLUF: 75.00 *********************** Table Stats:: Table: TIMES Alias: T #Rows: 1826 #Blks: 59 AvgRowLen: 197.00 Index Stats:: Index: TIMES_PK Col#: 1 LVLS: 1 #LB: 5 #DK: 1826 LB/K: 1.00 DB/K: 1.00 CLUF: 53.00 *********************** Table Stats:: Table: SALES Alias: S (Using composite stats) #Rows: 918843 #Blks: 1769 AvgRowLen: 29.00 Index Stats:: Index: SALES_CHANNEL_BIX Col#: 4 USING COMPOSITE STATS LVLS: 1 #LB: 47 #DK: 4 LB/K: 11.00 DB/K: 23.00 CLUF: 92.00 Index: SALES_CUST_BIX Col#: 2 USING COMPOSITE STATS LVLS: 1 #LB: 475 #DK: 7059 LB/K: 1.00 DB/K: 5.00 CLUF: 35808.00 Index: SALES_PROD_BIX Col#: 1 USING COMPOSITE STATS LVLS: 1 #LB: 32 #DK: 72 LB/K: 1.00 DB/K: 14.00 CLUF: 1074.00 Index: SALES_PROMO_BIX Col#: 5 USING COMPOSITE STATS LVLS: 1 #LB: 30 #DK: 4 LB/K: 7.00 DB/K: 13.00 CLUF: 54.00 Index: SALES_TIME_BIX Col#: 3 USING COMPOSITE STATS LVLS: 1 #LB: 59 #DK: 1460 LB/K: 1.00 DB/K: 1.00 CLUF: 1460.00 Access path analysis for SALES



IOTFRSPEED: 4096 bytes per millisecond (default is 4096) IOSEEKTIM: 10 milliseconds (default is 10)

*************************************** SINGLE TABLE ACCESS PATH Single Table Cardinality Estimation for SALES[S] Table: SALES Alias: S Card: Original: 918843.000000 Rounded: 918843 Computed: 918843.00 Non Adjusted: 918843.00 Access Path: TableScan Cost: 498.20 Resp: 498.20 Degree: 0 Cost_io: 481.00 Cost_cpu: 260685437 Resp_io: 481.00 Resp_cpu: 260685437 ****** trying bitmap/domain indexes ****** Access Path: index (FullScan) Index: SALES_CHANNEL_BIX resc_io: 75.00 resc_cpu: 552508 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 75.04 Resp: 75.04 Degree: 0 Access Path: index (FullScan) Index: SALES_CUST_BIX resc_io: 503.00 resc_cpu: 10743684 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 503.71 Resp: 503.71 Degree: 0 Access Path: index (FullScan) Index: SALES_PROD_BIX resc_io: 60.00 resc_cpu: 642086 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 60.04 Resp: 60.04 Degree: 0 Access Path: index (FullScan) Index: SALES_PROMO_BIX resc_io: 58.00 resc_cpu: 423844 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 58.03 Resp: 58.03 Degree: 0 Access Path: index (FullScan) Index: SALES_TIME_BIX resc_io: 60.00 resc_cpu: 719286 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 60.05 Resp: 60.05 Degree: 0 Access Path: index (FullScan) Index: SALES_PROMO_BIX resc_io: 58.00 resc_cpu: 423844 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 58.03 Access path: Bitmap index - accepted Cost: 2895.306181 Cost_io: 2869.400000 Cost_cpu: 392576474.936000 Sel: 1.000000 Not Believed to be index-only ****** finished trying bitmap/domain indexes ****** Best:: AccessPath: TableScan Cost: 498.20 Degree: 1 Resp: 498.20 Card: 918843.00 Bytes: 0 Access path analysis for TIMES *************************************** SINGLE TABLE ACCESS PATH Single Table Cardinality Estimation for TIMES[T] Table: TIMES Alias: T





Access path analysis for CUSTOMERS *************************************** SINGLE TABLE ACCESS PATH Single Table Cardinality Estimation for CUSTOMERS[C] Table: CUSTOMERS Alias: C Card: Original: 55500.000000 Rounded: 383 Computed: 382.76 Non Adjusted: 382.76 Access Path: TableScan Cost: 406.16 Resp: 406.16 Degree: 0 Cost_io: 404.00 Cost_cpu: 32782460 Resp_io: 404.00 Resp_cpu: 32782460 ****** trying bitmap/domain indexes ****** Access Path: index (FullScan) Index: CUSTOMERS_GENDER_BIX resc_io: 4.00 resc_cpu: 29486 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 4.00 Resp: 4.00 Degree: 0 Access Path: index (FullScan) Index: CUSTOMERS_MARITAL_BIX resc_io: 6.00 resc_cpu: 46329 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 6.00 Resp: 6.00 Degree: 0 Access Path: index (FullScan) Index: CUSTOMERS_PK resc_io: 116.00 resc_cpu: 11926087 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 116.79 Resp: 116.79 Degree: 0 Access Path: index (FullScan) Index: CUSTOMERS_YOB_BIX resc_io: 20.00 resc_cpu: 157429 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 20.01 Resp: 20.01 Degree: 0 Access Path: index (FullScan) Index: CUSTOMERS_GENDER_BIX resc_io: 4.00 resc_cpu: 29486 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 4.00 Resp: 4.00 Degree: 0 Access path: Bitmap index - accepted Cost: 2367.447569 Cost_io: 2364.560000 Cost_cpu: 43757572.166400 Sel: 1.000000 Not Believed to be index-only



Card: Original: 1826.000000 Rounded: 183 Computed: 182.60 Non Adjusted: 182.60 Access Path: TableScan Cost: 18.15 Resp: 18.15 Degree: 0 Cost_io: 18.00 Cost_cpu: 2314640 Resp_io: 18.00 Resp_cpu: 2314640 ****** trying bitmap/domain indexes ****** Access Path: index (FullScan) Index: TIMES_PK resc_io: 6.00 resc_cpu: 407929 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 6.03 Resp: 6.03 Degree: 0 ****** finished trying bitmap/domain indexes ****** Best:: AccessPath: TableScan Cost: 18.15 Degree: 1 Resp: 18.15 Card: 182.60 Bytes: 0

Practice 3-1: Understanding Optimizer Decisions (continued) ****** finished trying bitmap/domain indexes ****** Best:: AccessPath: TableScan Cost: 406.16 Degree: 1 Resp: 406.16 Card: 382.76

Bytes:

Access path analysis for CHANNELS *************************************** SINGLE TABLE ACCESS PATH Single Table Cardinality Estimation for CHANNELS[CH] Table: CHANNELS Alias: CH Card: Original: 5.000000 Rounded: 2 Computed: 2.00 Non Adjusted: 2.00 Access Path: TableScan Cost: 3.00 Resp: 3.00 Degree: 0 Cost_io: 3.00 Cost_cpu: 29826 Resp_io: 3.00 Resp_cpu: 29826 ****** trying bitmap/domain indexes ****** Access Path: index (FullScan) Index: CHANNELS_PK resc_io: 1.00 resc_cpu: 8121 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 1.00 Resp: 1.00 Degree: 0 ****** finished trying bitmap/domain indexes ****** Best:: AccessPath: TableScan Cost: 3.00 Degree: 1 Resp: 3.00 Card: 2.00 Bytes: 0 Grouping column cardinality [CHANNEL_CL] Grouping column cardinality [ CUST_CITY] Grouping column cardinality [CALENDAR_Q] ***************************************

2 286 2

OPTIMIZER STATISTICS AND COMPUTATIONS *************************************** GENERAL PLANS *************************************** Considering cardinality-based initial join order. Permutations for Starting Table :0 Join order[1]: CHANNELS[CH]#0 TIMES[T]#1 CUSTOMERS[C]#2 SALES[S]#3 *************** Now joining: TIMES[T]#1 *************** NL Join Outer table: Card: 2.00 Cost: 3.00 Resp: 3.00 21 Access path analysis for TIMES Inner table: TIMES Alias: T Access Path: TableScan NL Join: Cost: 37.31 Resp: 37.31 Degree: 1 Cost_io: 37.00 Cost_cpu: 4659106 Resp_io: 37.00 Resp_cpu: 4659106 ****** trying bitmap/domain indexes ****** Access Path: index (FullScan) Index: TIMES_PK resc_io: 6.00 resc_cpu: 407929

Degree: 1


Bytes:


0

Practice 3-1: Understanding Optimizer Decisions (continued) ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 6.03 Resp: 6.03 Degree: 0 ****** finished trying bitmap/domain indexes ******

*************** Now joining: CUSTOMERS[C]#2 *************** NL Join Outer table: Card: 365.20 Cost: 37.31 Resp: 37.31 Degree: 1 Bytes: 37 Access path analysis for CUSTOMERS Inner table: CUSTOMERS Alias: C Access Path: TableScan NL Join: Cost: 147725.92 Resp: 147725.92 Degree: 1 Cost_io: 146936.00 Cost_cpu: 11970256947 Resp_io: 146936.00 Resp_cpu: 11970256947 ****** trying bitmap/domain indexes ****** Access Path: index (FullScan) Index: CUSTOMERS_GENDER_BIX resc_io: 4.00 resc_cpu: 29486 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 4.00 Resp: 4.00 Degree: 0 Access Path: index (FullScan) Index: CUSTOMERS_MARITAL_BIX resc_io: 6.00 resc_cpu: 46329 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 6.00 Resp: 6.00 Degree: 0 Access Path: index (FullScan) Index: CUSTOMERS_PK resc_io: 116.00 resc_cpu: 11926087 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 116.79 Resp: 116.79 Degree: 0 Access Path: index (FullScan) Index: CUSTOMERS_YOB_BIX resc_io: 20.00 resc_cpu: 157429 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 Cost: 20.01 Resp: 20.01 Degree: 0 Access Path: index (FullScan) Index: CUSTOMERS_GENDER_BIX resc_io: 4.00 resc_cpu: 29486 ix_sel: 1.000000 ix_sel_with_filters: 1.000000 NL Join : Cost: 1498.02 Resp: 1498.02 Degree: 1 Cost_io: 1497.00 Cost_cpu: 15421408 Resp_io: 1497.00 Resp_cpu: 15421408 Access path: Bitmap index - accepted



Best NL cost: 37.31 resc: 37.31 resc_io: 37.00 resc_cpu: 4659106 resp: 37.31 resp_io: 37.00 resc_cpu: 4659106 Join Card: 365.200000 = = outer (2.000000) * inner (182.600000) * sel (1.000000) Join Card - Rounded: 365 Computed: 365.20 Grouping column cardinality [CHANNEL_CL] 2 Grouping column cardinality [ CUST_CITY] 286 Grouping column cardinality [CALENDAR_Q] 2 Best:: JoinMethod: NestedLoop Cost: 37.31 Degree: 1 Resp: 37.31 Card: 365.20 Bytes: 37


Best NL cost: 147725.92 resc: 147725.92 resc_io: 146936.00 resc_cpu: 11970256947 resp: 147725.92 resp_io: 146936.00 resc_cpu: 11970256947 Join Card: 139783.448276 = = outer (365.200000) * inner (382.758621) * sel (1.000000) Join Card - Rounded: 139783 Computed: 139783.45 Grouping column cardinality [CHANNEL_CL] 2 Grouping column cardinality [ CUST_CITY] 286 Grouping column cardinality [CALENDAR_Q] 2 Best:: JoinMethod: NestedLoop Cost: 147725.92 Degree: 1 Resp: 147725.92 Card: 139783.45 Bytes: 63 *************** Now joining: SALES[S]#3 *************** NL Join Outer table: Card: 139783.45 Cost: 147725.92 Resp: 147725.92 Degree: 1 Bytes: 63 Access path analysis for SALES Inner table: SALES Alias: S Access Path: TableScan NL Join: Cost: 2625413.78 Resp: 2625413.78 Degree: 1 Cost_io: 2538743.82 Cost_cpu: 1313377131608 Resp_io: 2538743.82 Resp_cpu: 1313377131608 ****** trying bitmap/domain indexes ****** Access Path: index (AllEqJoinGuess) Index: SALES_CHANNEL_BIX resc_io: 11.00 resc_cpu: 83786 ix_sel: 0.250000 ix_sel_with_filters: 0.250000 NL Join : Cost: 1686111.78 Resp: 1686111.78 Degree: 1 Cost_io: 1684549.00 Cost_cpu: 23682093020 Resp_io: 1684549.00 Resp_cpu: 23682093020 Access Path: index (AllEqJoinGuess) Index: SALES_CUST_BIX resc_io: 1.00 resc_cpu: 9171 ix_sel: 0.000142 ix_sel_with_filters: 0.000142 NL Join : Cost: 287593.52 Resp: 287593.52 Degree: 1 Cost_io: 286719.00 Cost_cpu: 13252268345 Resp_io: 286719.00 Resp_cpu: 13252268345 Access Path: index (AllEqJoinGuess) Index: SALES_TIME_BIX resc_io: 1.00 resc_cpu: 8171 ix_sel: 0.000685 ix_sel_with_filters: 0.000685 NL Join : Cost: 287584.29 Resp: 287584.29 Degree: 1 Cost_io: 286719.00 Cost_cpu: 13112485345 Resp_io: 286719.00 Resp_cpu: 13112485345 Access path: Bitmap index - accepted Cost: 723020.120275 Cost_io: 720497.059076 Cost_cpu: 38233905490.990532 Sel: 0.000000 Not Believed to be index-only ****** finished trying bitmap/domain indexes ******



Cost: 864192.977522 Cost_io: 863138.400000 Cost_cpu: 15980832052.096001 Sel: 1.000000 Not Believed to be index-only ****** finished trying bitmap/domain indexes ******

Best NL cost: 723020.12 resc: 723020.12 resc_io: 720497.06 resc_cpu: 38233905491 resp: 723020.12 resp_io: 720497.06 resc_cpu: 38233905491 Join Card: 3115.595241 = = outer (139783.448276) * inner (918843.000000) * sel (0.000000) Join Card - Rounded: 3116 Computed: 3115.60 Grouping column cardinality [CHANNEL_CL] 2 Grouping column cardinality [ CUST_CITY] 286 Grouping column cardinality [CALENDAR_Q] 2 Outer table: CUSTOMERS Alias: C resc: 147725.92 card 139783.45 bytes: 63 deg: 1 resp: 147725.92 Inner table: SALES Alias: S resc: 498.20 card: 918843.00 bytes: 21 deg: 1 resp: 498.20 using dmeth: 2 #groups: 1 SORT ressource Sort statistics Sort width: 238 Area size: 208896 Max Area size: 41943040 Degree: 1 Blocks to Sort: 1370 Row size: 80 Total Rows: 139783 Initial runs: 2 Merge passes: 1 IO Cost / pass: 744 Total IO sort cost: 2114 Total CPU sort cost: 156539686 Total Temp space used: 21423000 SORT ressource Sort statistics Sort width: 238 Area size: 208896 Max Area size: 41943040 Degree: 1 Blocks to Sort: 3825 Row size: 34 Total Rows: 918843 Initial runs: 2 Merge passes: 1 IO Cost / pass: 2074 Total IO sort cost: 5899 Total CPU sort cost: 929421655 Total Temp space used: 66626000 SM join: Resc: 156308.78 Resp: 156308.78 [multiMatchCost=0.00] SM Join SM cost: 156308.78 resc: 156308.78 resc_io: 155430.00 resc_cpu: 13316903726 resp: 156308.78 resp_io: 155430.00 resp_cpu: 13316903726 Outer table: CUSTOMERS Alias: C resc: 147725.92 card 139783.45 bytes: 63 deg: 1 resp: 147725.92 Inner table: SALES Alias: S resc: 498.20 card: 918843.00 bytes: 21 deg: 1 resp: 498.20 using dmeth: 2 #groups: 1 Cost per ptn: 1944.36 #ptns: 1 hash_area: 124 (max=10240) buildfrag: 1280 probefrag: 3702 ppasses: 1 Hash join: Resc: 150168.48 Resp: 150168.48 [multiMatchCost=0.00] HA Join HA cost: 150168.48 resc: 150168.48 resc_io: 149346.00 resc_cpu: 12463693737 resp: 150168.48 resp_io: 149346.00 resp_cpu: 12463693737 GROUP BY sort GROUP BY adjustment factor: 0.500000 GROUP BY cardinality: 572.000000, TABLE cardinality: 3116.000000 SORT ressource Sort statistics




Sort width: 238 Area size: 208896 Max Area size: 41943040 Degree: 1 Blocks to Sort: 40 Row size: 103 Total Rows: 3116 Initial runs: 1 Merge passes: 0 IO Cost / pass: 0 Total IO sort cost: 0 Total CPU sort cost: 16783070 Total Temp space used: 0 Best:: JoinMethod: Hash Cost: 150169.59 Degree: 1 Resp: 150169.59 Card: 3115.60 Bytes: 84 *********************** Best so far: Table#: 0 cost: 3.0020 card: 2.0000 bytes: 42 Table#: 1 cost: 37.3075 card: 365.2000 bytes: 13505 Table#: 2 cost: 147725.9191 card: 139783.4483 bytes: 8806329 Table#: 3 cost: 150169.5886 card: 3115.5952 bytes: 261744 *********************** Join order[2]: CHANNELS[CH]#0 TIMES[T]#1 SALES[S]#3 CUSTOMERS[C]#2 *************** Now joining: SALES[S]#3 *************** NL Join Outer table: Card: 365.20 Cost: 37.31 Resp: 37.31 Bytes: 37 Access path analysis for SALES Inner table: SALES Alias: S Access Path: TableScan NL Join: Cost: 6507.09 Resp: 6507.09 Degree: 1

Degree: 1

… *********************** Join order[22]: SALES[S]#3 CHANNELS[CH]#0

CUSTOMERS[C]#2

TIMES[T]#1

*************** Now joining: TIMES[T]#1 *************** NL Join Outer table: Card: 49822.22 Cost: 910.93 Resp: 910.93 Bytes: 47 Access path analysis for TIMES Inner table: TIMES Alias: T Access Path: TableScan NL Join: Cost: 804636.92 Resp: 804636.92 Degree: 1 Cost_io: 797001.00 Cost_cpu: 115712978623 Resp_io: 797001.00 Resp_cpu: 115712978623 Access Path: index (UniqueScan) Index: TIMES_PK resc_io: 1.00 resc_cpu: 10059 ix_sel: 0.000548 ix_sel_with_filters: 0.000548 NL Join : Cost: 50766.00 Resp: 50766.00 Degree: 1 Cost_io: 50707.00 Cost_cpu: 894143044


Degree: 1




Best NL cost: 50766.00 resc: 50766.00 resc_io: 50707.00 resc_cpu: 894143044 resp: 50766.00 resp_io: 50707.00 resc_cpu: 894143044 Join Card: 6231.190483 = = outer (49822.224013) * inner (182.600000) * sel (0.000685) Join Card - Rounded: 6231 Computed: 6231.19 Grouping column cardinality [CHANNEL_CL] 2 Grouping column cardinality [ CUST_CITY] 286 Grouping column cardinality [CALENDAR_Q] 2 Outer table: CUSTOMERS Alias: C resc: 910.93 card 49822.22 bytes: 47 deg: 1 resp: 910.93 Inner table: TIMES Alias: T resc: 18.15 card: 182.60 bytes: 16 deg: 1 resp: 18.15 using dmeth: 2 #groups: 1 SORT ressource Sort statistics Sort width: 238 Area size: 208896 Max Area size: 41943040 Degree: 1 Blocks to Sort: 379 Row size: 62 Total Rows: 49822 Initial runs: 2 Merge passes: 1 IO Cost / pass: 206 Total IO sort cost: 585 Total CPU sort cost: 59514576 Total Temp space used: 6022000 SORT ressource Sort statistics Sort width: 238 Area size: 208896 Max Area size: 41943040 Degree: 1 Blocks to Sort: 1 Row size: 28 Total Rows: 183 Initial runs: 1 Merge passes: 0 IO Cost / pass: 0 Total IO sort cost: 0 Total CPU sort cost: 15215743 Total Temp space used: 0 SM join: Resc: 1519.02 Resp: 1519.02 [multiMatchCost=0.00] SM Join SM cost: 1519.02 resc: 1519.02 resc_io: 1488.00 resc_cpu: 470031494 resp: 1519.02 resp_io: 1488.00 resp_cpu: 470031494 Outer table: CUSTOMERS Alias: C resc: 910.93 card 49822.22 bytes: 47 deg: 1 resp: 910.93 Inner table: TIMES Alias: T resc: 18.15 card: 182.60 bytes: 16 deg: 1 resp: 18.15 using dmeth: 2 #groups: 1 Cost per ptn: 141.09 #ptns: 1 hash_area: 124 (max=10240) buildfrag: 359 probefrag: 1 ppasses: 1 Hash join: Resc: 1070.22 Resp: 1070.22 [multiMatchCost=0.04] Outer table: TIMES Alias: T



Resp_io: 50707.00 Resp_cpu: 894143044 Access Path: index (AllEqUnique) Index: TIMES_PK resc_io: 1.00 resc_cpu: 10059 ix_sel: 0.000548 ix_sel_with_filters: 0.000548 NL Join : Cost: 50766.00 Resp: 50766.00 Degree: 1 Cost_io: 50707.00 Cost_cpu: 894143044 Resp_io: 50707.00 Resp_cpu: 894143044 ****** trying bitmap/domain indexes ****** ****** finished trying bitmap/domain indexes ******


*************** Now joining: CHANNELS[CH]#0 *************** NL Join Outer table: Card: 6231.19 Cost: 929.92 Resp: 929.92 Bytes: 63 Access path analysis for CHANNELS Inner table: CHANNELS Alias: CH Access Path: TableScan NL Join: Cost: 7694.18 Resp: 7694.18 Degree: 1 Cost_io: 7655.00 Cost_cpu: 593732024 Resp_io: 7655.00 Resp_cpu: 593732024 Access Path: index (UniqueScan) Index: CHANNELS_PK resc_io: 1.00 resc_cpu: 8451 ix_sel: 0.200000 ix_sel_with_filters: 0.200000 NL Join : Cost: 7164.39 Resp: 7164.39 Degree: 1 Cost_io: 7134.00 Cost_cpu: 460548636 Resp_io: 7134.00 Resp_cpu: 460548636 Access Path: index (AllEqUnique) Index: CHANNELS_PK resc_io: 1.00 resc_cpu: 8451 ix_sel: 0.200000 ix_sel_with_filters: 0.200000 NL Join : Cost: 7164.39 Resp: 7164.39 Degree: 1 Cost_io: 7134.00 Cost_cpu: 460548636 Resp_io: 7134.00 Resp_cpu: 460548636 ****** trying bitmap/domain indexes ****** ****** finished trying bitmap/domain indexes ******

Degree: 1

Best NL cost: 7164.39 resc: 7164.39 resc_io: 7134.00 resc_cpu: 460548636 resp: 7164.39 resp_io: 7134.00 resc_cpu: 460548636 Join Card: 3115.595241 = = outer (6231.190483) * inner (2.000000) * sel (0.250000) Join Card - Rounded: 3116 Computed: 3115.60 Grouping column cardinality [CHANNEL_CL] 2 Grouping column cardinality [ CUST_CITY] 286 Grouping column cardinality [CALENDAR_Q] 2 Outer table: TIMES Alias: T resc: 929.92 card 6231.19 bytes: 63 deg: 1 resp: 929.92 Inner table: CHANNELS Alias: CH



resc: 18.15 card 182.60 bytes: 16 deg: 1 resp: 18.15 Inner table: CUSTOMERS Alias: C resc: 910.93 card: 49822.22 bytes: 47 deg: 1 resp: 910.93 using dmeth: 2 #groups: 1 Cost per ptn: 0.83 #ptns: 1 hash_area: 124 (max=10240) buildfrag: 1 probefrag: 359 ppasses: 1 Hash join: Resc: 929.92 Resp: 929.92 [multiMatchCost=0.00] HA Join HA cost: 929.92 swapped resc: 929.92 resc_io: 903.00 resc_cpu: 407887714 resp: 929.92 resp_io: 903.00 resp_cpu: 407887714 Best:: JoinMethod: Hash Cost: 929.92 Degree: 1 Resp: 929.92 Card: 6231.19 Bytes: 63

resc: 3.00 card: 2.00 bytes: 21 deg: 1 resp: 3.00 using dmeth: 2 #groups: 1 SORT ressource Sort statistics Sort width: 238 Area size: 208896 Max Area size: 41943040 Degree: 1 Blocks to Sort: 62 Row size: 80 Total Rows: 6231 Initial runs: 2 Merge passes: 1 IO Cost / pass: 36 Total IO sort cost: 98 Total CPU sort cost: 20219323 Total Temp space used: 926000 SORT ressource Sort statistics Sort width: 238 Area size: 208896 Max Area size: 41943040 Degree: 1 Blocks to Sort: 1 Row size: 34 Total Rows: 2 Initial runs: 1 Merge passes: 0 IO Cost / pass: 0 Total IO sort cost: 0 Total CPU sort cost: 15153867 Total Temp space used: 0 SM join: Resc: 1033.25 Resp: 1033.25 [multiMatchCost=0.00] SM Join SM cost: 1033.25 resc: 1033.25 resc_io: 1004.00 resc_cpu: 443290729 resp: 1033.25 resp_io: 1004.00 resp_cpu: 443290729 Outer table: TIMES Alias: T resc: 929.92 card 6231.19 bytes: 63 deg: 1 resp: 929.92 Inner table: CHANNELS Alias: CH resc: 3.00 card: 2.00 bytes: 21 deg: 1 resp: 3.00 using dmeth: 2 #groups: 1 Cost per ptn: 0.56 #ptns: 1 hash_area: 124 (max=10240) buildfrag: 58 probefrag: 1 ppasses: 1 Hash join: Resc: 933.50 Resp: 933.50 [multiMatchCost=0.02] Outer table: CHANNELS Alias: CH resc: 3.00 card 2.00 bytes: 21 deg: 1 resp: 3.00 Inner table: TIMES Alias: T resc: 929.92 card: 6231.19 bytes: 63 deg: 1 resp: 929.92 using dmeth: 2 #groups: 1 Cost per ptn: 0.54 #ptns: 1 hash_area: 124 (max=10240) buildfrag: 1 probefrag: 58 ppasses: 1 Hash join: Resc: 933.46 Resp: 933.46 [multiMatchCost=0.00] HA Join HA cost: 933.46 swapped resc: 933.46 resc_io: 906.00 resc_cpu: 416117828 resp: 933.46 resp_io: 906.00 resp_cpu: 416117828 GROUP BY sort GROUP BY adjustment factor: 0.500000 GROUP BY cardinality: 572.000000, TABLE cardinality: 3116.000000 SORT ressource Sort statistics Sort width: 238 Area size: 208896 Max Area size: 41943040 Degree: 1 Blocks to Sort: 40 Row size: 103 Total Rows: 3116 Initial runs: 1 Merge passes: 0 IO Cost / pass: 0 Total IO sort cost: 0 Total CPU sort cost: 16783070 Total Temp space used: 0





********************************* Number of join permutations tried: 22 ********************************* (newjo-save) [1 3 2 0 ] GROUP BY adjustment factor: 0.500000 GROUP BY cardinality: 572.000000, TABLE cardinality: 3116.000000 SORT ressource Sort statistics Sort width: 238 Area size: 208896 Max Area size: 41943040 Degree: 1 Blocks to Sort: 40 Row size: 103 Total Rows: 3116 Initial runs: 1 Merge passes: 0 IO Cost / pass: 0 Total IO sort cost: 0 Total CPU sort cost: 16783070 Total Temp space used: 0 Trying or-Expansion on query block SEL$1 (#1) Transfer Optimizer annotations for query block SEL$1 (#1) id=0 frofand predicate="C"."CUST_STATE_PROVINCE"='CA' id=0 frofkksm[i] (sort-merge/hash) predicate="S"."CUST_ID"="C"."CUST_ID" id=0 frosand (sort-merge/hash) predicate="S"."CUST_ID"="C"."CUST_ID" id=0 frofkksm[i] (sort-merge/hash) predicate="S"."TIME_ID"="T"."TIME_ID" id=0 frosand (sort-merge/hash) predicate="S"."TIME_ID"="T"."TIME_ID" id=0 frofand predicate="T"."CALENDAR_QUARTER_DESC"='1999-Q1' OR "T"."CALENDAR_QUARTER_DESC"='1999-Q2' id=0 frofkksm[i] (sort-merge/hash) predicate="S"."CHANNEL_ID"="CH"."CHANNEL_ID" id=0 frosand (sort-merge/hash) predicate="S"."CHANNEL_ID"="CH"."CHANNEL_ID" id=0 frofand predicate="CH"."CHANNEL_DESC"='Catalog' OR "CH"."CHANNEL_DESC"='Internet' GROUP BY adjustment factor: 1.000000 Final cost for query block SEL$1 (#1) - All Rows Plan: Best join order: 16 Cost: 934.5672 Degree: 1 Card: 3116.0000 Bytes: 261744 Resc: 934.5672 Resc_io: 906.0000 Resc_cpu: 432900898 Resp: 934.5672 Resp_io: 906.0000 Resc_cpu: 432900898 kkoqbc-subheap (delete addr=0xb7d47960, in-use=105564, alloc=107812) kkoqbc-end: : call(in-use=124380, alloc=246544), compile(in-use=132500, alloc=136572), execution(in-use=3376, alloc=4060) kkoqbc: finish optimizing query block SEL$1 (#1) apadrv-end : call(in-use=124380, alloc=246544), compile(in-use=133196, alloc=136572), execution(in-use=3376, alloc=4060)

Starting SQL statement dump



Join order aborted: cost > best plan cost *********************** (newjo-stop-1) k:0, spcnt:0, perm:22, maxperm:2000

user_id=92 user_name=SH module=SQL*Plus action= sql_id=70fqjd9u1zk7c plan_hash_value=1647000731 problem_type=3 ----- Current SQL Statement for this session (sql_id=70fqjd9u1zk7c) ----SELECT ch.channel_class, c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold) sales_amount FROM sh.sales s,sh.times t,sh.customers c,sh.channels ch WHERE s.time_id = t.time_id AND s.cust_id = c.cust_id AND s.channel_id = ch.channel_id AND c.cust_state_province = 'CA' AND ch.channel_desc IN ('Internet','Catalog') AND t.calendar_quarter_desc IN ('1999-Q1','1999-Q2') GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc sql_text_length=473 sql=SELECT ch.channel_class, c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold) sales_amount FROM sh.sales s,sh.times t,sh.customers c,sh.channels ch WHERE s.time_id = t.time_id AND s.cust_id = c.cust_id AND s.channel_id = ch.channel_id sql=AND c.cust_state_province = 'CA' AND ch.channel_desc IN ('Internet','Catalog') AND t.calendar_quarter_desc IN ('1999-Q1','1999-Q2') GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc ----- Explain Plan Dump --------- Plan Table ----============ Plan Table ============ ----------------------------------------------------+----------------------------------+---------------+ | Id | Operation | Name | Rows | Bytes | Cost | Time | Pstart| Pstop | ----------------------------------------------------+----------------------------------+---------------+ | 0 | SELECT STATEMENT | | | | 935 | | | | | 1 | HASH GROUP BY | | 572 | 47K | 935 | 00:00:12 | | | | 2 | HASH JOIN | | 3116 | 256K | 933 | 00:00:12 | | | | 3 | TABLE ACCESS FULL | CHANNELS | 2 | 42 | 3 | 00:00:01 | | | | 4 | HASH JOIN | | 6231 | 383K | 930 | 00:00:12 | | | | 5 | PART JOIN FILTER CREATE | :BF0000 | 183 | 2928 | 18 | 00:00:01 | | | | 6 | TABLE ACCESS FULL | TIMES | 183 | 2928 | 18 | 00:00:01 | | | | 7 | HASH JOIN | | 49K | 2287K | 911 | 00:00:11 | | | | 8 | TABLE ACCESS FULL | CUSTOMERS| 383 | 9958 | 406 | 00:00:05 | | |




| 9 | PARTITION RANGE JOIN-FILTER | | 897K | 18M | 498 | 00:00:06 | :BF0000| :BF0000| | 10 | TABLE ACCESS FULL | SALES | 897K | 18M | 498 | 00:00:06 | :BF0000| :BF0000| ----------------------------------------------------+----------------------------------+---------------+ Predicate Information: ---------------------2 - access("S"."CHANNEL_ID"="CH"."CHANNEL_ID") 3 - filter(("CH"."CHANNEL_DESC"='Catalog' OR "CH"."CHANNEL_DESC"='Internet')) 4 - access("S"."TIME_ID"="T"."TIME_ID") 6 - filter(("T"."CALENDAR_QUARTER_DESC"='1999-Q1' OR "T"."CALENDAR_QUARTER_DESC"='1999-Q2')) 7 - access("S"."CUST_ID"="C"."CUST_ID") 8 - filter("C"."CUST_STATE_PROVINCE"='CA') Content of other_xml column =========================== db_version : 11.1.0.6 parse_schema : SH plan_hash : 1647000731 plan_hash_2 : 94088042 Outline Data: /*+ BEGIN_OUTLINE_DATA IGNORE_OPTIM_EMBEDDED_HINTS OPTIMIZER_FEATURES_ENABLE('11.1.0.6') DB_VERSION('11.1.0.6') ALL_ROWS OUTLINE_LEAF(@"SEL$1") FULL(@"SEL$1" "C"@"SEL$1") FULL(@"SEL$1" "S"@"SEL$1") FULL(@"SEL$1" "T"@"SEL$1") FULL(@"SEL$1" "CH"@"SEL$1") LEADING(@"SEL$1" "C"@"SEL$1" "S"@"SEL$1" "T"@"SEL$1" "CH"@"SEL$1") USE_HASH(@"SEL$1" "S"@"SEL$1") USE_HASH(@"SEL$1" "T"@"SEL$1") USE_HASH(@"SEL$1" "CH"@"SEL$1") SWAP_JOIN_INPUTS(@"SEL$1" "T"@"SEL$1") SWAP_JOIN_INPUTS(@"SEL$1" "CH"@"SEL$1") USE_HASH_AGGREGATION(@"SEL$1") END_OUTLINE_DATA */ Optimizer state dump: Compilation Environment Dump optimizer_mode_hinted optimizer_features_hinted parallel_execution_enabled parallel_query_forced_dop parallel_dml_forced_dop parallel_ddl_forced_degree parallel_ddl_forced_instances _query_rewrite_fudge optimizer_features_enable

= = = = = = = = =

false 0.0.0 true 0 0 0 0 90 11.1.0.6




Practice 3-1: Understanding Optimizer Decisions (continued) … Bug Fix Control Environment fix 3834770 = 1 fix 3746511 = enabled fix 4519016 = enabled fix 3118776 = enabled fix 4488689 = enabled fix 2194204 = disabled fix 2660592 = enabled

Query Block Registry: SEL$1 0xb7e0905c (PARSER) [FINAL] : call(in-use=143844, alloc=246544), compile(in-use=166732, alloc=224788), execution(in-use=13796, alloc=16288) End of Optimizer State Dump ====================== END SQL Statement Dump ====================== [oracle@edrsr33p1-orcl Trace_Event]$

3) Execute the te_cleanup.sh script to clean up your environment for this lab. [oracle@edrsr33p1-orcl Trace_Event]$ ./te_cleanup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Wed Apr 9 22:18:01 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Trace_Event]$



…




Practice 4-1: Using Different Access Paths In this practice, you explore various access paths the optimizer can use, and compare them. You have the possibility of exploring 16 different scenarios, each of which are selfcontained. All scripts needed for this lab can be found in your $HOME/solutions/Access_Paths directory. 1) Case 1: Connected as the oracle user from a terminal session, execute the ap_setup.sh script. [oracle@edrsr33p1-orcl Access_Paths]$ ./ap_setup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Wed Apr 9 14:24:51 2008 All rights reserved.

Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> alter user sh identified by sh account unlock; User altered. SQL> SQL> grant dba to sh; Grant succeeded. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Access_Paths]$

2) In the same terminal session, connect as the SH user in the SQL*Plus session. [oracle@edrsr33p1-orcl Access_Paths]$ sqlplus sh/sh SQL*Plus: Release 11.1.0.6.0 - Production on Wed Apr 9 14:24:58 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL>




Practice 4-1: Using Different Access Paths (continued) 3) Unless otherwise notified, stay connected to your SQL*Plus session as the SH user. Execute the idx_setup.sql script to set up your environment for case 1. SQL> @idx_setup SQL> SQL> drop table mysales purge; drop table mysales purge * ERROR at line 1: ORA-00942: table or view does not exist

Table created. SQL> SQL> insert into mysales select * from mysales; 918843 rows created. SQL> commit; Commit complete. SQL> SQL> SQL> insert into mysales select * from mysales; 1837686 rows created. SQL> commit; Commit complete. SQL> SQL> insert into mysales select * from mysales; 3675372 rows created. SQL> commit; Commit complete. SQL> SQL> insert into mysales select * from mysales; 7350744 rows created. SQL> commit; Commit complete. SQL> SQL> insert into mysales select * from mysales;



SQL> SQL> create table mysales as select * from sh.sales;

Practice 4-1: Using Different Access Paths (continued) 14701488 rows created. SQL> commit; Commit complete. SQL> SQL> insert into mysales values (0,0,sysdate,0,0,0,0); 1 row created. SQL> commit;

SQL> SQL> exec dbms_stats.gather_schema_stats('SH'); PL/SQL procedure successfully completed. SQL>

4) Set up your session with the following commands: set timing on, set autotrace trace only, and set linesize 200. After this, execute the select * from mysales where prod_id=0; query. What do you observe? a) Basically, there are no indexes on the MYSALES table. b) .The only possibility for the optimizer is to use the full table scan to retrieve only one row. You can see that the scan takes a long time. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL>

@with_and_without_index set echo on set timing on set autotrace traceonly set linesize 200 pagesize 1000 alter system flush shared_pool;

System altered. Elapsed: 00:00:00.61 SQL> alter system flush buffer_cache; System altered. Elapsed: 00:00:15.04 SQL> SQL> select * from mysales where prod_id=0; Elapsed: 00:00:28.85 Execution Plan ---------------------------------------------------------Plan hash value: 3597614299



Commit complete.

Practice 4-1: Using Different Access Paths (continued) ---------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ---------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 402K| 11M| 40249 (2)| 00:08:03 | |* 1 | TABLE ACCESS FULL| MYSALES | 402K| 11M| 40249 (2)| 00:08:03 | ----------------------------------------------------------------------------

1 - filter("PROD_ID"=0)

Statistics ---------------------------------------------------------421 recursive calls 0 db block gets 141606 consistent gets 141529 physical reads 0 redo size 790 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 5 sorts (memory) 0 sorts (disk) 1 rows processed SQL> SQL> set timing off SQL> set autotrace off SQL>

5) How do you enhance the performance of the query in step 4? Implement your solution. SQL> @create_mysales_index SQL> set echo on SQL> SQL> create index mysales_prodid_idx on mysales(prod_id) nologging compute statistics; Index created. SQL>

6) Execute the same query again and verify that performance is enhanced now. a) After implementing the index, the optimizer can use it to speed up the query execution time. You can see a dramatic improvement in performance. SQL> @with_and_without_index SQL> set echo on



Predicate Information (identified by operation id): ---------------------------------------------------

Practice 4-1: Using Different Access Paths (continued) SQL> SQL> SQL> SQL> SQL> SQL>

set timing on set autotrace traceonly set linesize 200 pagesize 1000 alter system flush shared_pool;

System altered. Elapsed: 00:00:00.29 SQL> alter system flush buffer_cache;

Elapsed: 00:00:01.71 SQL> SQL> select * from mysales where prod_id=0; Elapsed: 00:00:00.88 Execution Plan ---------------------------------------------------------Plan hash value: 3009203711 ------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 402K| 11M| 6079 (1)| 00:01:13 | | 1 | TABLE ACCESS BY INDEX ROWID| MYSALES | 402K| 11M| 6079 (1)| 00:01:13 | |* 2 | INDEX RANGE SCAN | MYSALES_PRODID_IDX | 402K| | 822 (1)| 00:00:10 | ------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - access("PROD_ID"=0)

Statistics ---------------------------------------------------------496 recursive calls 0 db block gets 104 consistent gets 21 physical reads 0 redo size 794 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 6 sorts (memory) 0 sorts (disk)



System altered.

Practice 4-1: Using Different Access Paths (continued) 1

rows processed

SQL> SQL> set timing off SQL> set autotrace off SQL>

7) Clean up your environment for case 1 by executing the idx_cleanup.sql script. SQL> @idx_cleanup SQL> set echo on SQL> SQL> drop table mysales purge;

SQL> SQL>

8) Case 2: Drop all indexes currently created on the CUSTOMERS table except its primary key index. SQL> @drop_customers_indexes SQL> set termout off SQL> -------------------------------------------------------------set store save set

termout off set sqlplus_settings replace buffer.sql replace timing off heading off verify off autotrace off feedback off

spool

dait.sql

SELECT 'drop index '||i.index_name||';' FROM user_indexes i WHERE i.table_name = 'CUSTOMERS' AND NOT EXISTS (SELECT 'x' FROM user_constraints c WHERE c.index_name = i.index_name AND c.table_name = i.table_name AND c.status = 'ENABLED'); spool @dait

off

get buffer.sql nolist @sqlplus_settings set termout on



Table dropped.

Practice 4-1: Using Different Access Paths (continued) 9) Execute the following query: SELECT /*+ FULL(c) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 AND cust_credit_limit = 10000;

What do you observe? a) The optimizer uses a full table scan and the cost for this query is relatively high. @query00 set echo on set timing on set autotrace traceonly set linesize 200 pagesize 1000 SELECT /*+ FULL(c) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 AND cust_credit_limit = 10000 /

6 rows selected. Elapsed: 00:00:00.29 Execution Plan ---------------------------------------------------------Plan hash value: 2008213504 -----------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -----------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 6 | 1080 | 407 (1)| 00:00:05 | |* 1 | TABLE ACCESS FULL| CUSTOMERS | 6 | 1080 | 407 (1)| 00:00:05 | -----------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 - filter(TO_NUMBER("CUST_POSTAL_CODE")=40804 AND "CUST_CREDIT_LIMIT"=10000 AND "CUST_GENDER"='M')

Statistics ---------------------------------------------------------1067 recursive calls 0 db block gets 1722 consistent gets



SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5 6

Practice 4-1: Using Different Access Paths (continued) 1461 116 2570 420 2 27 0 6

physical reads redo size bytes sent via SQL*Net to client bytes received via SQL*Net from client SQL*Net roundtrips to/from client sorts (memory) sorts (disk) rows processed

10) Create three B*-tree indexes on the following CUSTOMERS table columns: cust_gender cust_postal_code cust_credit_limit SQL> SQL> SQL> SQL> 2 3

@create_cust_gender_index set echo on CREATE INDEX cust_cust_gender_idx ON customers(cust_gender) NOLOGGING COMPUTE STATISTICS;

Index created. SQL> SQL> SQL> SQL> SQL> 2 3

@create_cust_postal_code_index set echo on CREATE INDEX cust_cust_postal_code_idx ON customers(cust_postal_code) NOLOGGING COMPUTE STATISTICS;


@create_cust_credit_limit_index set echo on CREATE INDEX cust_cust_credit_limit_idx ON customers(cust_credit_limit) NOLOGGING COMPUTE STATISTICS;

Index created. SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4

@list_customers_indexes set echo on set linesize 200 pagesize 1000 SELECT ,

ui.table_name decode(ui.index_type ,'NORMAL', ui.uniqueness ,ui.index_type) AS index_type




Practice 4-1: Using Different Access Paths (continued) , ui.index_name FROM user_indexes ui WHERE ui.table_name = 'CUSTOMERS' ORDER BY ui.table_name , ui.uniqueness desc;

TABLE_NAME INDEX_NAME -------------------------------------------------CUSTOMERS CUSTOMERS_PK CUSTOMERS CUST_CUST_GENDER_IDX CUSTOMERS CUST_CUST_CREDIT_LIMIT_IDX CUSTOMERS CUST_CUST_POSTAL_CODE_IDX

INDEX_TYPE --------------------------- --------UNIQUE NONUNIQUE NONUNIQUE NONUNIQUE

SQL>

11) Start monitoring all the CUSTOMERS indexes. SQL> @start_monitoring_indexes SQL> set echo on SQL> SQL> ALTER INDEX CUSTOMERS_PK MONITORING USAGE; Index altered. SQL> SQL> ALTER INDEX CUST_CUST_POSTAL_CODE_IDX MONITORING USAGE; Index altered. SQL> SQL> ALTER INDEX CUST_CUST_GENDER_IDX MONITORING USAGE; Index altered. SQL> SQL> ALTER INDEX CUST_CUST_CREDIT_LIMIT_IDX MONITORING USAGE; Index altered. SQL> SQL> SQL> SQL> SQL> SQL> SQL>

@show_index_usage set echo on set linesize 200 select * from v$object_usage;

INDEX_NAME TABLE_NAME MON USE START_MONITORING END_MONITORING ------------------------------ ------------------------------ --- -- ------------------- -------------------



5 6 7 8 9

Practice 4-1: Using Different Access Paths (continued) CUSTOMERS_PK 04/09/2008 14:52:43 CUST_CUST_POSTAL_CODE_IDX 04/09/2008 14:52:43 CUST_CUST_GENDER_IDX 04/09/2008 14:52:43 CUST_CUST_CREDIT_LIMIT_IDX 04/09/2008 14:52:43

CUSTOMERS

YES NO

CUSTOMERS

YES NO

CUSTOMERS

YES NO

CUSTOMERS

YES NO

SQL>

SELECT /*+ INDEX(c) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 AND cust_credit_limit = 10000;

What do you observe? a) The optimizer chooses to use only one index to do a fast full scan. The cost is lower than the full table scan. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5 6

@query01 set echo on set timing on set autotrace traceonly set linesize 200 pagesize 1000 SELECT /*+ INDEX(c) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 AND cust_credit_limit = 10000 /

6 rows selected. Elapsed: 00:00:00.04 Execution Plan ---------------------------------------------------------Plan hash value: 1928091631 -------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 6 | 1080 | 218 (1)| 00:00:03 | |* 1 | TABLE ACCESS BY INDEX ROWID| CUSTOMERS | 6 | 1080 | 218 (1)| 00:00:03 | |* 2 | INDEX FULL SCAN | CUST_CUST_POSTAL_CODE_IDX | 89 | | 134 (1)| 00:00:02 |



12) Execute the following query:

Practice 4-1: Using Different Access Paths (continued) -------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): ---------------------------------------------------


13) Execute the following query: SELECT /*+ INDEX_COMBINE(c) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 AND cust_credit_limit = 10000;

What do you observe? a) This time the optimizer uses multiple indexes and combines them to access the table. However, the cost is higher than that from the previous step as well as the full table scan. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5 6

@query02 set echo on set linesize 200 pagesize 1000 set timing on set autotrace traceonly SELECT /*+ INDEX_COMBINE(c) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 AND cust_credit_limit = 10000 /

6 rows selected.



1 - filter("CUST_CREDIT_LIMIT"=10000 AND "CUST_GENDER"='M') 2 - filter(TO_NUMBER("CUST_POSTAL_CODE")=40804)

Practice 4-1: Using Different Access Paths (continued) Elapsed: 00:00:00.06

-------------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 6 | 1080 | 466 (1)| 00:00:06 | |* 1 | TABLE ACCESS BY INDEX ROWID | CUSTOMERS | 6 | 1080 | 466 (1)| 00:00:06 | | 2 | BITMAP CONVERSION TO ROWIDS | | | | | | | 3 | BITMAP AND | | | | | | | 4 | BITMAP CONVERSION FROM ROWIDS| | | | | | |* 5 | INDEX RANGE SCAN | CUST_CUST_CREDIT_LIMIT_IDX | | | 14 (0)| 00:00:01 | | 6 | BITMAP CONVERSION FROM ROWIDS| | | | | | |* 7 | INDEX RANGE SCAN | CUST_CUST_GENDER_IDX | | | 51 (0)| 00:00:01 | -------------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 - filter(TO_NUMBER("CUST_POSTAL_CODE")=40804) 5 - access("CUST_CREDIT_LIMIT"=10000) 7 - access("CUST_GENDER"='M')

Statistics ---------------------------------------------------------3 recursive calls 7 db block gets 894 consistent gets 81 physical reads 1020 redo size 2570 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 6 rows processed SQL> SQL> set autotrace off SQL> set timing off SQL>



Execution Plan ---------------------------------------------------------Plan hash value: 4093665856

Practice 4-1: Using Different Access Paths (continued) 14) Confirm the list of indexes that were accessed in this case. @show_index_usage set echo on set linesize 200 select * from v$object_usage;

INDEX_NAME TABLE_NAME USE START_MONITORING END_MONITORING ------------------------------ ------------------------------ ------------------- ------------------CUSTOMERS_PK CUSTOMERS 04/09/2008 14:52:43 CUST_CUST_POSTAL_CODE_IDX CUSTOMERS YES 04/09/2008 14:52:43 CUST_CUST_GENDER_IDX CUSTOMERS YES 04/09/2008 14:52:43 CUST_CUST_CREDIT_LIMIT_IDX CUSTOMERS YES 04/09/2008 14:52:43

MON --- -YES NO YES YES YES

SQL> SQL>

15) Case 3: Drop all the CUSTOMERS indexes except its primary key index. After this, make sure you create a concatenated index on the following CUSTOMERS columns, and in the order mentioned here: cust_gender cust_credit_limit cust_postal_code SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3

@drop_customers_indexes set termout off @create_gender_limit_code_index set echo on CREATE INDEX cust_gender_limit_code_idx ON customers(cust_gender,cust_credit_limit,cust_postal_code) NOLOGGING COMPUTE STATISTICS;

Index created. SQL>

16) Execute the following query: SELECT /*+ INDEX(c) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 AND cust_credit_limit = 10000;

What do you observe? a) The optimizer uses your concatenated index, and the resulting cost is by far the best compared to the previous steps. Oracle Database 11g: SQL Tuning Workshop A - 70


SQL> SQL> SQL> SQL> SQL> SQL>

Practice 4-1: Using Different Access Paths (continued) SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5 6

@query01 set echo on set timing on set autotrace traceonly set linesize 200 pagesize 1000 SELECT /*+ INDEX(c) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 AND cust_credit_limit = 10000 /

Elapsed: 00:00:00.01 Execution Plan ---------------------------------------------------------Plan hash value: 2871279522 --------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 7 | 1260 | 18 (0)| 00:00:01 | | 1 | TABLE ACCESS BY INDEX ROWID| CUSTOMERS | 7 | 1260 | 18 (0)| 00:00:01 | |* 2 | INDEX RANGE SCAN | CUST_GENDER_LIMIT_CODE_IDX | 6 | | 12 (0)| 00:00:01 | --------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - access("CUST_GENDER"='M' AND "CUST_CREDIT_LIMIT"=10000) filter(TO_NUMBER("CUST_POSTAL_CODE")=40804)

Statistics ---------------------------------------------------------1 recursive calls 0 db block gets 22 consistent gets 14 physical reads 0 redo size 2981 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 6 rows processed



6 rows selected.

Practice 4-1: Using Different Access Paths (continued) SQL> SQL> set timing off SQL> set autotrace off SQL>

17) Execute the following query: SELECT /*+ INDEX(c) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_credit_limit = 10000;

a) The query is almost the same as in the previous step, but the predicate is removed. The optimizer can still use the concatenated index, but the resulting cost is much higher because cust_credit_limit is not very selective. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5

@query03 set echo on set linesize 200 pagesize 1000 set timing on set autotrace traceonly SELECT /*+ INDEX(c) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_credit_limit = 10000 /

4101 rows selected. Elapsed: 00:00:00.08 Execution Plan ---------------------------------------------------------Plan hash value: 2871279522 --------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 3469 | 609K| 3454 (1)| 00:00:42 | | 1 | TABLE ACCESS BY INDEX ROWID| CUSTOMERS | 3469 | 609K| 3454 (1)| 00:00:42 | |* 2 | INDEX RANGE SCAN | CUST_GENDER_LIMIT_CODE_IDX | 3469 | | 12 (0)| 00:00:01 | --------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): ---------------------------------------------------



What do you observe?

Practice 4-1: Using Different Access Paths (continued)

Statistics ---------------------------------------------------------1 recursive calls 0 db block gets 4391 consistent gets 0 physical reads 0 redo size 795172 bytes sent via SQL*Net to client 3423 bytes received via SQL*Net from client 275 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 4101 rows processed SQL> SQL> SQL> set autotrace off SQL> set timing off SQL>

18) Execute the following query: SELECT /*+ INDEX(c) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804;

What do you observe? a) You replaced cust_credit_limit with cust_postal_code, which has better selectivity. The index is used and the resulting cost is better. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5

@query04 set echo on set timing on set autotrace traceonly set linesize 200 pagesize 1000 SELECT /*+ INDEX(c) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 /

75 rows selected. Elapsed: 00:00:00.02 Execution Plan ---------------------------------------------------------Plan hash value: 2871279522 ---------------------------------------------------------------------------------------------------------



2 - access("CUST_GENDER"='M' AND "CUST_CREDIT_LIMIT"=10000)

Practice 4-1: Using Different Access Paths (continued) | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 45 | 8100 | 133 (1)| 00:00:02 | | 1 | TABLE ACCESS BY INDEX ROWID| CUSTOMERS | 45 | 8100 | 133 (1)| 00:00:02 | |* 2 | INDEX RANGE SCAN | CUST_GENDER_LIMIT_CODE_IDX | 45 | | 87 (0)| 00:00:02 | ---------------------------------------------------------------------------------------------------------

2 - access("CUST_GENDER"='M') filter(TO_NUMBER("CUST_POSTAL_CODE")=40804)


19) Execute the following query: SELECT /*+ INDEX(c) */ c.* FROM customers c WHERE cust_postal_code = 40804 AND cust_credit_limit = 10000;

What do you observe? a) The leading part of the concatenated index is no longer part of the query. However, the optimizer is still able to use the index by doing a fast full index scan. Nevertheless, the resulting cost is not the best. SQL> SQL> SQL> SQL> SQL> SQL> SQL>

@query05 set echo on set timing on set autotrace traceonly set linesize 200 pagesize 1000




Practice 4-1: Using Different Access Paths (continued) SQL> 2 3 4 5

SELECT FROM WHERE AND /

/*+ INDEX(c) */ c.* customers c cust_postal_code = 40804 cust_credit_limit = 10000

15 rows selected. Elapsed: 00:00:00.02

--------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 11 | 1980 | 185 (1)| 00:00:03 | | 1 | TABLE ACCESS BY INDEX ROWID| CUSTOMERS | 11 | 1980 | 185 (1)| 00:00:03 | |* 2 | INDEX FULL SCAN | CUST_GENDER_LIMIT_CODE_IDX | 11 | | 173 (1)| 00:00:03 | --------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - access("CUST_CREDIT_LIMIT"=10000) filter(TO_NUMBER("CUST_POSTAL_CODE")=40804 AND "CUST_CREDIT_LIMIT"=10000)

Statistics ---------------------------------------------------------1 recursive calls 0 db block gets 189 consistent gets 56 physical reads 0 redo size 4617 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 15 rows processed SQL> SQL> set timing off SQL> set autotrace off SQL> SQL>





SQL> @drop_customers_indexes SQL> set termout off SQL> SQL> @create_cust_gender_bindex SQL> set echo on SQL> SQL> CREATE BITMAP INDEX cust_cust_gender_bidx ON customers(cust_gender) 2 NOLOGGING COMPUTE STATISTICS; Index created. SQL> SQL> @create_cust_postal_code_bindex SQL> set echo on SQL> SQL> CREATE BITMAP INDEX cust_cust_postal_code_bidx ON customers(cust_postal_code) 2 NOLOGGING COMPUTE STATISTICS; Index created. SQL> SQL> @create_cust_credit_limit_bindex SQL> set echo on SQL> SQL> CREATE BITMAP INDEX cust_cust_credit_limit_bidx ON customers(cust_credit_limit) 2 NOLOGGING COMPUTE STATISTICS; Index created. SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5 6 7 8 9

@list_customers_indexes set echo on set linesize 200 pagesize 1000 SELECT ,

ui.table_name decode(ui.index_type ,'NORMAL', ui.uniqueness ,ui.index_type) AS index_type , ui.index_name FROM user_indexes ui WHERE ui.table_name = 'CUSTOMERS' ORDER BY ui.table_name , ui.uniqueness desc;

TABLE_NAME INDEX_NAME

INDEX_TYPE



20) Case 4: Drop all the CUSTOMERS indexes except its primary key index. After this, create three different bitmap indexes on the following columns of the CUSTOMERS table: cust_gender cust_postal_code cust_credit_limit

Practice 4-1: Using Different Access Paths (continued) -------------------------------------------------CUSTOMERS CUSTOMERS_PK CUSTOMERS CUST_CUST_GENDER_BIDX CUSTOMERS CUST_CUST_CREDIT_LIMIT_BIDX CUSTOMERS CUST_CUST_POSTAL_CODE_BIDX

--------------------------- --------UNIQUE BITMAP BITMAP BITMAP

SQL>

SELECT /*+ INDEX_COMBINE(c) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 AND cust_credit_limit = 10000;

What do you observe? a) The optimizer uses only two bitmap indexes to solve this query. However, the cost is not a good one. It is a little lesser than cost of the full table scan. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5 6

@query02 set echo on set linesize 200 pagesize 1000 set timing on set autotrace traceonly SELECT /*+ INDEX_COMBINE(c) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 AND cust_credit_limit = 10000 /

6 rows selected. Elapsed: 00:00:00.01 Execution Plan ---------------------------------------------------------Plan hash value: 3047829365 ----------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ----------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 6 | 1080 | 402 (1)| 00:00:05 | |* 1 | TABLE ACCESS BY INDEX ROWID | CUSTOMERS | 6 | 1080 | 402 (1)| 00:00:05 |




Practice 4-1: Using Different Access Paths (continued) | 2 | BITMAP CONVERSION TO ROWIDS| | | | | | | 3 | BITMAP AND | | | | | | |* 4 | BITMAP INDEX SINGLE VALUE| CUST_CUST_CREDIT_LIMIT_BIDX | | | | | |* 5 | BITMAP INDEX SINGLE VALUE| CUST_CUST_GENDER_BIDX | | | | | -----------------------------------------------------------------------------------------------------------

1 - filter(TO_NUMBER("CUST_POSTAL_CODE")=40804) 4 - access("CUST_CREDIT_LIMIT"=10000) 5 - access("CUST_GENDER"='M')

Statistics ---------------------------------------------------------1 recursive calls 0 db block gets 813 consistent gets 5 physical reads 0 redo size 2570 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 6 rows processed SQL> SQL> set autotrace off SQL> set timing off SQL> SQL>

22) Case 5: Drop all the CUSTOMERS indexes except its primary key index. After this, create two bitmap indexes on the following columns of the CUSTOMERS table: cust_year_of_birth cust_credit_limit SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3

@drop_customers_indexes set termout off @create_cust_year_of_birth_bindex set echo on CREATE BITMAP INDEX cust_cust_year_of_birth_bidx ON customers(cust_year_of_birth) NOLOGGING COMPUTE STATISTICS;

Index created. SQL>




Practice 4-1: Using Different Access Paths (continued) SQL> @create_cust_credit_limit_bindex SQL> set echo on SQL> SQL> CREATE BITMAP INDEX cust_cust_credit_limit_bidx ON customers(cust_credit_limit) 2 NOLOGGING COMPUTE STATISTICS; Index created. SQL>

SELECT /*+ INDEX_COMBINE(c) */ c.* FROM customers c WHERE c.cust_year_of_birth = 1953 OR c.cust_credit_limit = 10000;

What do you observe? a) The query uses an OR construct. The optimizer can use both bitmap indexes. However, this resulting cost is not the best. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5

@query06 set echo on set linesize 200 set timing on set autotrace traceonly SELECT /*+ INDEX_COMBINE(c) */ c.* FROM customers c WHERE c.cust_year_of_birth = 1953 OR c.cust_credit_limit = 10000 /

7158 rows selected. Elapsed: 00:00:00.12 Execution Plan ---------------------------------------------------------Plan hash value: 1912490408 -----------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -----------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 7585 | 1333K| 581 (1)| 00:00:07 | | 1 | TABLE ACCESS BY INDEX ROWID | CUSTOMERS | 7585 | 1333K| 581 (1)| 00:00:07 | | 2 | BITMAP CONVERSION TO ROWIDS| | | | | | | 3 | BITMAP OR | | | | | |




Practice 4-1: Using Different Access Paths (continued) |* 4 | BITMAP INDEX SINGLE VALUE| CUST_CUST_CREDIT_LIMIT_BIDX | | | | | |* 5 | BITMAP INDEX SINGLE VALUE| CUST_CUST_YEAR_OF_BIRTH_BIDX | | | | | -----------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): ---------------------------------------------------

Statistics ---------------------------------------------------------1 recursive calls 0 db block gets 1683 consistent gets 3 physical reads 0 redo size 1391886 bytes sent via SQL*Net to client 5667 bytes received via SQL*Net from client 479 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 7158 rows processed SQL> SQL> set timing off SQL> set autotrace off SQL> SQL>

24) Case 6: Drop all the CUSTOMERS indexes except its primary key index. After this, create three different bitmap indexes on the following columns of the CUSTOMERS table: cust_year_of_birth cust_credit_limit cust_postal_code SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3

@drop_customers_indexes set termout off @create_cust_year_of_birth_bindex set echo on CREATE BITMAP INDEX cust_cust_year_of_birth_bidx ON customers(cust_year_of_birth) NOLOGGING COMPUTE STATISTICS;

Index created. SQL> SQL> @create_cust_credit_limit_bindex SQL> set echo on



4 - access("C"."CUST_CREDIT_LIMIT"=10000) 5 - access("C"."CUST_YEAR_OF_BIRTH"=1953)

Practice 4-1: Using Different Access Paths (continued) SQL> SQL> CREATE BITMAP INDEX cust_cust_credit_limit_bidx ON customers(cust_credit_limit) 2 NOLOGGING COMPUTE STATISTICS; Index created.

Index created. SQL>

25) Execute the following query: SELECT c.* FROM customers c WHERE (c.cust_year_of_birth = '1970' And c.cust_postal_code 40804 ) AND NOT cust_credit_limit = 15000;

=

What do you observe? a) The query has a complex WHERE clause that is well suited for using bitmap indexes. The optimizer uses two bitmap indexes and the resulting cost is better than the full table scan cost. SQL> @query07 SQL> set echo on SQL> SQL> set timing on SQL> set autotrace traceonly SQL> SQL> SELECT c.* 2 FROM customers c 3 WHERE (c.cust_year_of_birth = '1970' And c.cust_postal_code 40804 ) 4 AND NOT cust_credit_limit = 15000 5 /

=

Elapsed: 00:00:00.03 Execution Plan ---------------------------------------------------------Plan hash value: 576122600 ------------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------------------------------



SQL> SQL> @create_cust_postal_code_bindex SQL> set echo on SQL> SQL> CREATE BITMAP INDEX cust_cust_postal_code_bidx ON customers(cust_postal_code) 2 NOLOGGING COMPUTE STATISTICS;

| 0 | SELECT STATEMENT | | 1 | 180 | 133 (0)| 00:00:02 | |* 1 | TABLE ACCESS BY INDEX ROWID | CUSTOMERS | 1 | 180 | 133 (0)| 00:00:02 | | 2 | BITMAP CONVERSION TO ROWIDS | | | | | | | 3 | BITMAP MINUS | | | | | | | 4 | BITMAP MINUS | | | | | | |* 5 | BITMAP INDEX SINGLE VALUE| CUST_CUST_YEAR_OF_BIRTH_BIDX | | | | | |* 6 | BITMAP INDEX SINGLE VALUE| CUST_CUST_CREDIT_LIMIT_BIDX | | | | | |* 7 | BITMAP INDEX SINGLE VALUE | CUST_CUST_CREDIT_LIMIT_BIDX | | | | | ------------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 5 6 7

-

filter(TO_NUMBER("C"."CUST_POSTAL_CODE")=40804) access("C"."CUST_YEAR_OF_BIRTH"=1970) access("CUST_CREDIT_LIMIT"=15000) access("CUST_CREDIT_LIMIT" IS NULL)


26) Make sure the optimizer can no longer use the bitmap index you created on the cust_year_of_birth column. a) The best solution is to render it invisible. SQL> show parameter optimizer_use_invisible_indexes NAME TYPE VALUE ------------------------------------ ----------- -----------------------------




Practice 4-1: Using Different Access Paths (continued) optimizer_use_invisible_indexes boolean FALSE SQL> alter index cust_cust_year_of_birth_bidx invisible; Index altered. SQL> select index_name, visibility from user_indexes where table_owner='SH' and table_name='CUSTOMERS'; VISIBILIT --------VISIBLE INVISIBLE VISIBLE VISIBLE

4 rows selected. SQL>

27) Execute the following query: SELECT c.* FROM customers c WHERE (c.cust_year_of_birth = '1970' And c.cust_postal_code 40804 ) AND NOT cust_credit_limit = 15000;

=

What do you observe? a) This is the same query as in the previous step. However, the optimizer can no longer find a good plan that uses bitmap indexes. SQL> @query07 SQL> set echo on SQL> SQL> set timing on SQL> set autotrace traceonly SQL> SQL> SELECT c.* 2 FROM customers c 3 WHERE (c.cust_year_of_birth = '1970' And c.cust_postal_code 40804 ) 4 AND NOT cust_credit_limit = 15000 5 /

=

Elapsed: 00:00:00.03 Execution Plan ---------------------------------------------------------Plan hash value: 2008213504 -----------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -----------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 180 | 407 (1)| 00:00:05 |



INDEX_NAME -----------------------------CUST_CUST_CREDIT_LIMIT_BIDX CUST_CUST_YEAR_OF_BIRTH_BIDX CUST_CUST_POSTAL_CODE_BIDX CUSTOMERS_PK

Practice 4-1: Using Different Access Paths (continued) |* 1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 180 | 407 (1)| 00:00:05 | -----------------------------------------------------------------------------Predicate Information (identified by operation id): ---------------------------------------------------


28) Case 7: Execute the following query: SELECT c.* FROM customers c WHERE cust_id IN (88340,104590,44910);

What do you observe? a) The optimizer can use the CUSTOMERS primary key index to solve this query. The cost is very low for the resulting plan. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4

@query08 set echo on set timing on set linesize 200 set autotrace traceonly SELECT c.* FROM customers c WHERE cust_id IN (88340,104590,44910) /

Elapsed: 00:00:00.07 Execution Plan ----------------------------------------------------------



1 - filter(TO_NUMBER("C"."CUST_POSTAL_CODE")=40804 AND "C"."CUST_YEAR_OF_BIRTH"=1970 AND "CUST_CREDIT_LIMIT"<>15000)

Practice 4-1: Using Different Access Paths (continued) -------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 3 | 540 | 7 (0)| 00:00:01 | | 1 | INLIST ITERATOR | | | | | | | 2 | TABLE ACCESS BY INDEX ROWID| CUSTOMERS | 3 | 540 | 7 (0)| 00:00:01 | |* 3 | INDEX UNIQUE SCAN | CUSTOMERS_PK | 3 | | 4 (0)| 00:00:01 | -------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------3 - access("CUST_ID"=44910 OR "CUST_ID"=88340 OR "CUST_ID"=104590)


29) Case 8: Drop all the indexes on the CUSTOMERS table except its primary key index. After this, create a concatenated B*-tree index on the following columns of the CUSTOMERS table, and in the order here: cust_last_name cust_first_name SQL> SQL> SQL> SQL> SQL>

@drop_customers_indexes set termout off @create_last_first_name_index set echo on



Plan hash value: 293792914

Practice 4-1: Using Different Access Paths (continued) SQL> SQL> CREATE INDEX cust_last_first_name_idx 2 ON customers(cust_last_name,cust_first_name) 3 NOLOGGING COMPUTE STATISTICS; Index created. SQL>

30) Execute the following query: SELECT c.cust_last_name , c.cust_first_name FROM customers c;

a) The optimizer can use only the index without accessing the table itself. The resulting cost is very good. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4

@query09 set echo on set linesize 200 set timing on set autotrace traceonly SELECT c.cust_last_name , c.cust_first_name FROM customers c /

55500 rows selected. Elapsed: 00:00:00.19 Execution Plan ---------------------------------------------------------Plan hash value: 445338993 -----------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -----------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 55500 | 812K| 55 (2)| 00:00:01 | | 1 | INDEX FAST FULL SCAN| CUST_LAST_FIRST_NAME_IDX | 55500 | 812K| 55 (2)| 00:00:01 | ------------------------------------------------------------------------------------------------





Practice 4-1: Using Different Access Paths (continued) 193 0 792248 41109 3701 0 0 55500


31) Case 9: Drop all the indexes on the CUSTOMERS table except its primary key index. After this, create two B*-tree indexes on the following columns of the CUSTOMERS table: cust_last_name cust_first_name SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3

@drop_customers_indexes set termout off @create_last_name_index set echo on CREATE INDEX cust_cust_last_name_idx ON customers(cust_last_name) NOLOGGING COMPUTE STATISTICS;


@create_first_name_index set echo on CREATE INDEX cust_cust_first_name_idx ON customers(cust_first_name) NOLOGGING COMPUTE STATISTICS;

Index created. SQL>

32) Execute the following query: SELECT /*+ INDEX_JOIN(c cust_cust_first_name_idx cust_cust_last_name_idx) */ c.cust_last_name , c.cust_first_name FROM customers c;

What do you observe? a) Although the optimizer can use both the indexes, the resulting cost is not better than the concatenated index case.



SQL> SQL> SQL> set autotrace off SQL> set timing off SQL> SQL>

Practice 4-1: Using Different Access Paths (continued) SQL> @query10 SQL> set echo on SQL> SQL> set linesize 200 SQL> set timing on SQL> set autotrace traceonly SQL> SQL> SELECT /*+ INDEX_JOIN(c cust_cust_first_name_idx cust_cust_last_name_idx) */ c.cust_last_name 2 , c.cust_first_name 3 FROM customers c 4 /

Elapsed: 00:00:00.27 Execution Plan ---------------------------------------------------------Plan hash value: 3557918892 -------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 55500 | 812K| 511 (1)| 00:00:07 | | 1 | VIEW | index$_join$_001 | 55500 | 812K| 511 (1)| 00:00:07 | |* 2 | HASH JOIN | | | | | | | 3 | INDEX FAST FULL SCAN| CUST_CUST_FIRST_NAME_IDX | 55500 | 812K| 175 (1)| 00:00:03 | | 4 | INDEX FAST FULL SCAN| CUST_CUST_LAST_NAME_IDX | 55500 | 812K| 178 (0)| 00:00:03 | -------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - access(ROWID=ROWID)

Statistics ---------------------------------------------------------1 recursive calls 0 db block gets 3985 consistent gets 279 physical reads 0 redo size 811440 bytes sent via SQL*Net to client 41109 bytes received via SQL*Net from client 3701 SQL*Net roundtrips to/from client 0 sorts (memory)



55500 rows selected.

Practice 4-1: Using Different Access Paths (continued) 0 55500

sorts (disk) rows processed


SQL> @drop_customers_indexes SQL> set termout off SQL> SQL> @create_cust_credit_limit_bindex SQL> set echo on SQL> SQL> CREATE BITMAP INDEX cust_cust_credit_limit_bidx ON customers(cust_credit_limit) 2 NOLOGGING COMPUTE STATISTICS; Index created. SQL>

34) Execute the following query: SELECT count(*) credit_limit FROM customers WHERE cust_credit_limit = 10000;

What do you observe? a) Although cust_credit_limit is not a selective column, the COUNT operation on its bitmap index is very efficient. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4

@query11 set echo on set linesize 200 set timing on set autotrace traceonly SELECT count(*) credit_limit FROM customers WHERE cust_credit_limit = 10000 /

Elapsed: 00:00:00.00 Execution Plan ---------------------------------------------------------Plan hash value: 37937133



33) CASE 10: Drop all the indexes on the CUSTOMERS table except its primary key index. Then, create one bitmap index on the following column of the CUSTOMERS table: cust_credit_limit

---------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ---------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 4 | 1 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 4 | | | | 2 | BITMAP CONVERSION COUNT | | 6938 | 27752 | 1 (0)| 00:00:01 | |* 3 | BITMAP INDEX SINGLE VALUE| CUST_CUST_CREDIT_LIMIT_BIDX | | | | | ---------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------3 - access("CUST_CREDIT_LIMIT"=10000)

Statistics ---------------------------------------------------------1 recursive calls 0 db block gets 3 consistent gets 2 physical reads 0 redo size 423 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 1 rows processed SQL> SQL> SQL> set autotrace off SQL> set timing off SQL> SQL>

35) Case 11: Drop all the CUSTOMERS indexes except its primary key index. After this, create one B*-tree index on the following column of the CUSTOMERS table: cust_credit_limit SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3

@drop_customers_indexes set termout off @create_cust_credit_limit_index set echo on CREATE INDEX cust_cust_credit_limit_idx ON customers(cust_credit_limit) NOLOGGING COMPUTE STATISTICS;




Practice 4-1: Using Different Access Paths (continued) Index created. SQL>

36) Execute the following query: SELECT count(*) credit_limit FROM customers WHERE cust_credit_limit = 10000;


SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4

@query11 set echo on set linesize 200 set timing on set autotrace traceonly SELECT count(*) credit_limit FROM customers WHERE cust_credit_limit = 10000 /

Elapsed: 00:00:00.00 Execution Plan ---------------------------------------------------------Plan hash value: 3421880850 ----------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ----------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 4 | 14 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 4 | | | |* 2 | INDEX RANGE SCAN| CUST_CUST_CREDIT_LIMIT_IDX | 6938 | 27752 | 14 (0)| 00:00:01 | ----------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - access("CUST_CREDIT_LIMIT"=10000)

Statistics ---------------------------------------------------------1 recursive calls 0 db block gets



a) The optimizer can still use the index; however, this is less efficient compared to the corresponding bitmap index from the previous case.

Practice 4-1: Using Different Access Paths (continued) consistent gets physical reads redo size bytes sent via SQL*Net to client bytes received via SQL*Net from client SQL*Net roundtrips to/from client sorts (memory) sorts (disk) rows processed


37) Case 12: Drop all the indexes on the CUSTOMERS table except its primary key index. After this, create one B*-tree index on the following column of the CUSTOMERS table: cust_last_name SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3

@drop_customers_indexes set termout off @create_last_name_index set echo on CREATE INDEX cust_cust_last_name_idx ON customers(cust_last_name) NOLOGGING COMPUTE STATISTICS;

Index created. SQL>

38) Execute the following query: SELECT cust_id, country_id FROM customers WHERE LOWER( cust_last_name) LIKE 'gentle';

What do you observe? a) Although there is an index, it cannot be used because its column is modified by a function. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4

@query12 set echo on set linesize 200 set timing on set autotrace traceonly SELECT cust_id, country_id FROM customers WHERE LOWER( cust_last_name) LIKE 'gentle' /



14 13 0 423 420 2 0 0 1

Practice 4-1: Using Different Access Paths (continued) 80 rows selected. Elapsed: 00:00:00.01

-----------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -----------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 555 | 9990 | 406 (1)| 00:00:05 | |* 1 | TABLE ACCESS FULL| CUSTOMERS | 555 | 9990 | 406 (1)| 00:00:05 | -----------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 - filter(LOWER("CUST_LAST_NAME")='gentle')


39) How can you enhance the performance of the previous query without modifying the statement itself? Implement your solution. a) You can create a function-based index. SQL> SQL> SQL> SQL> 2 3

@create_lower_cust_last_name_index set echo on CREATE INDEX lower_cust_last_name_idx ON customers(LOWER(cust_last_name)) /




Practice 4-1: Using Different Access Paths (continued) Index created. SQL>

40) Check if your solution executes faster than in the case of the query in step 38. @query12 set echo on set linesize 200 set timing on set autotrace traceonly SELECT cust_id, country_id FROM customers WHERE LOWER( cust_last_name) LIKE 'gentle' /

80 rows selected. Elapsed: 00:00:00.00 Execution Plan ---------------------------------------------------------Plan hash value: 967065894 ------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 555 | 17760 | 41 (0)| 00:00:01 | | 1 | TABLE ACCESS BY INDEX ROWID| CUSTOMERS | 555 | 17760 | 41 (0)| 00:00:01 | |* 2 | INDEX RANGE SCAN | LOWER_CUST_LAST_NAME_IDX | 222 | | 1 (0)| 00:00:01 | ------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - access(LOWER("CUST_LAST_NAME")='gentle')

Statistics ---------------------------------------------------------24 recursive calls 0 db block gets 23 consistent gets 1 physical reads 0 redo size 2077 bytes sent via SQL*Net to client 475 bytes received via SQL*Net from client 7 SQL*Net roundtrips to/from client



SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4

Practice 4-1: Using Different Access Paths (continued) 0 0 80

sorts (memory) sorts (disk) rows processed

SQL> SQL> set autotrace off SQL> set timing off SQL> SQL>

41) Case 13: Execute the iot_setup.sql script to set up the environment for this case. @iot_setup set echo on CREATE table promotions_iot (promo_id number primary key , promo_name VARCHAR2(40) , promo_subcategory VARCHAR2 (30) , promo_category VARCHAR2 (30) , promo_cost NUMBER , promo_begin_date DATE , promo_end_date DATE) ORGANIZATION INDEX /

Table created. SQL> SQL> INSERT INTO promotions_iot 2 SELECT promo_id, promo_name, promo_subcategory, promo_category, promo_cost, promo_begin_date, promo_end_date 3 FROM promotions 4 / 503 rows created. SQL>

42) Execute the following two queries: SELECT * FROM promotions WHERE promo_id > 300; SELECT /*+ INDEX(promotions) */ * FROM promotions WHERE promo_id > 300;

What do you observe? a) The first lets the optimizer decide the plan, and the best it can find is to do a full table scan. Forcing the use of the index is not a good idea, as it takes longer to execute. SQL> @query13 SQL> set echo on SQL>



SQL> SQL> SQL> SQL> 2 3 4 5 6 7 8 9 10

Practice 4-1: Using Different Access Paths (continued) SQL> SQL> SQL> SQL> SQL> 2 3 4

set linesize 200 set timing on set autotrace traceonly SELECT * FROM promotions WHERE promo_id > 300 /

235 rows selected.

Execution Plan ---------------------------------------------------------Plan hash value: 4106015420 ------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 364 | 35308 | 17 (0)| 00:00:01 | |* 1 | TABLE ACCESS FULL| PROMOTIONS | 364 | 35308 | 17 (0)| 00:00:01 | ------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 - filter("PROMO_ID">300)

Statistics ---------------------------------------------------------123 recursive calls 0 db block gets 88 consistent gets 3 physical reads 0 redo size 21829 bytes sent via SQL*Net to client 585 bytes received via SQL*Net from client 17 SQL*Net roundtrips to/from client 4 sorts (memory) 0 sorts (disk) 235 rows processed SQL> SQL> 2 3 4

SELECT /*+ INDEX(promotions) */ * FROM promotions WHERE promo_id > 300 /

235 rows selected.



Elapsed: 00:00:00.02


----------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ----------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 364 | 35308 | 353 (0)| 00:00:05 | | 1 | TABLE ACCESS BY INDEX ROWID| PROMOTIONS | 364 | 35308 | 353 (0)| 00:00:05 | |* 2 | INDEX RANGE SCAN | PROMO_PK | 364 | | 1 (0)| 00:00:01 | ----------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - access("PROMO_ID">300)


43) Execute the following query: SELECT * FROM promotions_iot WHERE promo_id > 300;

What do you observe? a) The optimizer directly uses the index-organized structure, which is extremely efficient in this case compared to the previous step. SQL> @query14




Practice 4-1: Using Different Access Paths (continued) SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4

set echo on set linesize 200 set timing on set autotrace traceonly SELECT * FROM promotions_iot WHERE promo_id > 300 /

235 rows selected.

Execution Plan ---------------------------------------------------------Plan hash value: 1463021396 ------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 235 | 23500 | 2 (0)| 00:00:01 | |* 1 | INDEX RANGE SCAN| SYS_IOT_TOP_72170 | 235 | 23500 | 2 (0)| 00:00:01 | ------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 - access("PROMO_ID">300) Note ----- dynamic sampling used for this statement

Statistics ---------------------------------------------------------5 recursive calls 0 db block gets 42 consistent gets 0 physical reads 116 redo size 19922 bytes sent via SQL*Net to client 585 bytes received via SQL*Net from client 17 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 235 rows processed SQL>



Elapsed: 00:00:00.00

Practice 4-1: Using Different Access Paths (continued) SQL> set autotrace off SQL> set timing off SQL>

44) Execute the iot_cleanup.sql script to clean up your environment. SQL> @iot_cleanup SQL> set echo on SQL> SQL> drop table promotions_iot purge; Table dropped.

45) Case 14: Execute shc_setup.sql to set up your environment for this lab. SQL> @shc_setup SQL> set echo on SQL> SQL> set linesize 200 SQL> SQL> drop cluster bigemp_cluster including tables; drop cluster bigemp_cluster including tables * ERROR at line 1: ORA-00943: cluster does not exist

SQL> SQL> 2 3 4 5

CREATE CLUSTER bigemp_cluster (deptno number, sal number sort) HASHKEYS 10000 single table HASH IS deptno SIZE 50 tablespace users;

Cluster created. SQL> SQL> create table bigemp_fact ( 2 empno number primary key, sal number sort, job varchar2(12) not null, 3 deptno number not null, hiredate date not null) 4 CLUSTER bigemp_cluster (deptno, sal); Table created. SQL> SQL> SQL> 2 3 4 5 6 7

begin for i in 1..1400000 loop insert into bigemp_fact values(i,i,'J1',10,sysdate); end loop; commit; end; /



SQL> SQL>

Practice 4-1: Using Different Access Paths (continued) PL/SQL procedure successfully completed. SQL> SQL> 2 3 4 5 6 7

begin for i in 1..1400000 loop insert into bigemp_fact values(1400000+i,i,'J1',20,sysdate); end loop; commit; end; /

SQL> SQL> SQL> exec dbms_stats.gather_schema_stats('SH'); PL/SQL procedure successfully completed. SQL>

46) Execute the query15.sql script. What do you observe? a) Because you may have a lot of memory on your system, the script first reduces the amount of memory available to your session. The optimizer decides to use the cluster access path to retrieve the data. The cost is minimal. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL>

@query15 set echo on set linesize 200 set timing on set autotrace traceonly alter session set workarea_size_policy=manual;

Session altered. Elapsed: 00:00:00.02 SQL> alter session set sort_area_size=50000; Session altered. Elapsed: 00:00:00.01 SQL> SQL> alter system flush shared_pool; System altered. Elapsed: 00:00:00.16 SQL> alter system flush buffer_cache; System altered. Elapsed: 00:00:06.69 SQL> SQL>



PL/SQL procedure successfully completed.

Practice 4-1: Using Different Access Paths (continued) SQL> select * from bigemp_fact where deptno=10; 1400000 rows selected. Elapsed: 00:00:07.21

-------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1400K| 32M| 1 (0)| 00:00:01 | |* 1 | TABLE ACCESS HASH| BIGEMP_FACT | 1400K| 32M| 1 (0)| 00:00:01 | -------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 - access("DEPTNO"=10)


47) Execute the query16.sql script. What do you observe? a) Again, the script first ensures that the amount of memory available to your session is reduced. Then the script executes the same query, but asks for ordering the result based on the sorted sal column. The optimizer can still use the cluster access path without sorting the data. The cost is still minimal. SQL> @query16 SQL> set echo on




Practice 4-1: Using Different Access Paths (continued) SQL> SQL> SQL> SQL> SQL> SQL>

set linesize 200 set timing on set autotrace traceonly alter session set workarea_size_policy=manual;

Session altered. Elapsed: 00:00:00.00 SQL> alter session set sort_area_size=50000;

Elapsed: 00:00:00.00 SQL> SQL> alter system flush shared_pool; System altered. Elapsed: 00:00:00.10 SQL> alter system flush buffer_cache; System altered. Elapsed: 00:00:00.04 SQL> SQL> select * from bigemp_fact where deptno=10 order by sal; 1400000 rows selected. Elapsed: 00:00:07.41 Execution Plan ---------------------------------------------------------Plan hash value: 865757019 -------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1400K| 32M| 1 (0)| 00:00:01 | |* 1 | TABLE ACCESS HASH| BIGEMP_FACT | 1400K| 32M| 1 (0)| 00:00:01 | -------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 - access("DEPTNO"=10)

Statistics



Session altered.


SQL> SQL> set autotrace off SQL> set timing off SQL>

48) Execute the query17.sql script. What do you observe? a) Again, the script first ensures that the amount of memory available to your session is reduced. Then the script executes the same query, but asks to order the result based on the sorted sal column in the descending order. The optimizer can still use the cluster access path without sorting the data. The cost is still minimal. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL>


Session altered. Elapsed: 00:00:00.00 SQL> alter session set sort_area_size=50000; Session altered. Elapsed: 00:00:00.00 SQL> SQL> alter system flush shared_pool; System altered. Elapsed: 00:00:00.09 SQL> alter system flush buffer_cache; System altered. Elapsed: 00:00:00.12 SQL> SQL> select * from bigemp_fact where deptno=10 order by sal desc; 1400000 rows selected.



---------------------------------------------------------1090 recursive calls 10 db block gets 99512 consistent gets 6012 physical reads 0 redo size 33605911 bytes sent via SQL*Net to client 1027083 bytes received via SQL*Net from client 93335 SQL*Net roundtrips to/from client 12 sorts (memory) 0 sorts (disk) 1400000 rows processed


-------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1400K| 32M| 1 (0)| 00:00:01 | |* 1 | TABLE ACCESS HASH| BIGEMP_FACT | 1400K| 32M| 1 (0)| 00:00:01 | -------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 - access("DEPTNO"=10)


49) Execute the query18.sql script. What do you observe? a) Again, the script first ensures that the amount of memory available to your session is reduced. Then the script executes the same query but this time asks to order the result based on the nonsorted empno column. The optimizer can still make use of the cluster access path, but must sort the data making the cost of the query higher. SQL> SQL> SQL> SQL> SQL>

@query18 set echo on set linesize 200 set timing on




Practice 4-1: Using Different Access Paths (continued) SQL> set autotrace traceonly SQL> SQL> alter session set workarea_size_policy=manual; Session altered. Elapsed: 00:00:00.00 SQL> alter session set sort_area_size=50000; Session altered.

System altered. Elapsed: 00:00:00.10 SQL> alter system flush buffer_cache; System altered. Elapsed: 00:00:00.04 SQL> SQL> select * from bigemp_fact where deptno=10 order by empno; 1400000 rows selected. Elapsed: 00:00:10.01 Execution Plan ---------------------------------------------------------Plan hash value: 1775608660 ----------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time | ----------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1400K| 32M| | 47728 (1)| 00:09:33 | | 1 | SORT ORDER BY | | 1400K| 32M| 107M| 47728 (1)| 00:09:33 | |* 2 | TABLE ACCESS HASH| BIGEMP_FACT | 1400K| 32M| | 1 (0)| 00:00:01 | ----------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - access("DEPTNO"=10)

Statistics ----------------------------------------------------------



Elapsed: 00:00:00.00 SQL> SQL> alter system flush shared_pool;

Practice 4-1: Using Different Access Paths (continued) recursive calls db block gets consistent gets physical reads redo size bytes sent via SQL*Net to client bytes received via SQL*Net from client SQL*Net roundtrips to/from client sorts (memory) sorts (disk) rows processed

SQL> SQL> set autotrace off SQL> set timing off SQL>

50) Execute the query19.sql script. What do you observe? a) Again, the script first ensures that the amount of memory available to your session is reduced. Then the script executes the same query, but this time asks to order the result based on the sal, deptno key. The optimizer can still make use of the cluster access path, but must sort the data making the cost of the query higher. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL>


Session altered. Elapsed: 00:00:00.00 SQL> alter session set sort_area_size=50000; Session altered. Elapsed: 00:00:00.00 SQL> SQL> alter system flush shared_pool; System altered. Elapsed: 00:00:00.10 SQL> alter system flush buffer_cache; System altered. Elapsed: 00:00:00.09 SQL> SQL> select * from bigemp_fact where deptno=10 order by sal,empno; 1400000 rows selected.



1139 12 6178 12238 0 33605911 1027083 93335 12 1 1400000


----------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time | ----------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1400K| 32M| | 47728 (1)| 00:09:33 | | 1 | SORT ORDER BY | | 1400K| 32M| 107M| 47728 (1)| 00:09:33 | |* 2 | TABLE ACCESS HASH| BIGEMP_FACT | 1400K| 32M| | 1 (0)| 00:00:01 | ----------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - access("DEPTNO"=10)


51) Execute the shc_cleanup.sql script to clean up your environment. SQL> @shc_cleanup SQL> set echo on SQL> SQL> drop cluster bigemp_cluster including tables; Cluster dropped. SQL> SQL>




Practice 4-1: Using Different Access Paths (continued) 52) Case 15: Execute the nic_setup.sql script to set up your environment for this case.

SQL> SQL> drop table emp purge; drop table emp purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> drop table dept purge; drop table dept purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> SQL> SQL> CREATE TABLE 2 empno 3 ename 4 job 5 mgr 6 hiredate 7 sal 8 comm 9 deptno 10 );

emp ( NUMBER(7) , VARCHAR2(15) NOT NULL, VARCHAR2(9) , NUMBER(7) , DATE , NUMBER(7) , NUMBER(7) , NUMBER(3)

Table created. SQL> SQL> CREATE TABLE dept ( 2 deptno NUMBER(3) , 3 dname VARCHAR2(14), 4 loc VARCHAR2(14), 5 c VARCHAR2(500) 6 ); Table created. SQL> SQL> CREATE INDEX emp_index 2 ON emp(deptno) 3 TABLESPACE users



SQL> @nic_setup SQL> set echo on SQL> SQL> drop cluster emp_dept including tables; drop cluster emp_dept including tables * ERROR at line 1: ORA-00943: cluster does not exist

Practice 4-1: Using Different Access Paths (continued) 4 5 6 7 8

STORAGE (INITIAL 50K NEXT 50K MINEXTENTS 2 MAXEXTENTS 10 PCTINCREASE 33);

SQL> SQL> CREATE INDEX dept_index 2 ON dept(deptno) 3 TABLESPACE users 4 STORAGE (INITIAL 50K 5 NEXT 50K 6 MINEXTENTS 2 7 MAXEXTENTS 10 8 PCTINCREASE 33); Index created. SQL> SQL> SQL> begin 2 for i in 1..999 loop 3 insert into dept values (i,'D'||i,'L'||i,dbms_random.string('u',500)); 4 end loop; 5 commit; 6 end; 7 / PL/SQL procedure successfully completed. SQL> SQL> SQL> begin 2 for i in 1..500000 loop 3 insert into emp values (i,dbms_random.string('u',15),dbms_random.string('u',9),i,sysdate,i, i,mod(i,999)); 4 end loop; 5 commit; 6 end; 7 / PL/SQL procedure successfully completed. SQL> SQL> exec dbms_stats.gather_schema_stats('SH'); PL/SQL procedure successfully completed. SQL>

53) Execute the nic_query.sql script. What do you observe?



Index created.

Practice 4-1: Using Different Access Paths (continued) a) The script first ensures that the amount of memory available to your session is reduced. Then the script executes a join between the EMP and DEPT tables. The optimizer is able to make use of the index to resolve the join. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL>

@nic_query set echo on set timing on set autotrace traceonly set linesize 200 alter session set workarea_size_policy=manual;

Elapsed: 00:00:00.00 SQL> alter session set sort_area_size=50000; Session altered. Elapsed: 00:00:00.00 SQL> alter session set hash_area_size=5000; Session altered. Elapsed: 00:00:00.00 SQL> SQL> SQL> select * from emp,dept where emp.deptno=dept.deptno and emp.deptno > 800; 99000 rows selected. Elapsed: 00:00:02.88 Execution Plan ---------------------------------------------------------Plan hash value: 128236434 -------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time | -------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 19780 | 10M| | 3449 (1)| 00:00:42 | |* 1 | HASH JOIN | | 19780 | 10M| 104K| 3449 (1)| 00:00:42 | | 2 | TABLE ACCESS BY INDEX ROWID| DEPT | 199 | 99K| | 18 (0)| 00:00:01 | |* 3 | INDEX RANGE SCAN | DEPT_INDEX | 199 | | | 2 (0)| 00:00:01 | |* 4 | TABLE ACCESS FULL | EMP | 99198 | 5521K| | 1207 (2)| 00:00:15 | --------------------------------------------------------------------------------------------------



Session altered.

Practice 4-1: Using Different Access Paths (continued) Predicate Information (identified by operation id): ---------------------------------------------------

Statistics ---------------------------------------------------------9 recursive calls 0 db block gets 4365 consistent gets 10146 physical reads 0 redo size 57968984 bytes sent via SQL*Net to client 73009 bytes received via SQL*Net from client 6601 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 99000 rows processed SQL> SQL> set autotrace off SQL> set timing off; SQL>

54) How would you enhance the performance of the previous query? Implement your solution. a) Create a cluster to store the two tables. SQL> @ic_setup SQL> set echo on SQL> SQL> drop table emp purge; Table dropped. SQL> drop table dept purge; Table dropped. SQL> SQL> drop cluster emp_dept including tables; drop cluster emp_dept including tables * ERROR at line 1: ORA-00943: cluster does not exist

SQL> SQL> CREATE CLUSTER emp_dept (deptno NUMBER(3)) 2 SIZE 600 3 TABLESPACE users 4 STORAGE (INITIAL 200K 5 NEXT 300K



1 - access("EMP"."DEPTNO"="DEPT"."DEPTNO") 3 - access("DEPT"."DEPTNO">800) 4 - filter("EMP"."DEPTNO">800)


MINEXTENTS 2 PCTINCREASE 33);

SQL> SQL> CREATE TABLE emp ( 2 empno NUMBER(7) , 3 ename VARCHAR2(15) NOT NULL, 4 job VARCHAR2(9) , 5 mgr NUMBER(7) , 6 hiredate DATE , 7 sal NUMBER(7) , 8 comm NUMBER(7) , 9 deptno NUMBER(3)) 10 CLUSTER emp_dept (deptno); Table created. SQL> SQL> CREATE TABLE dept ( 2 deptno NUMBER(3) , 3 dname VARCHAR2(14), 4 loc VARCHAR2(14), 5 c VARCHAR2(500)) 6 CLUSTER emp_dept (deptno); Table created. SQL> SQL> CREATE INDEX emp_dept_index 2 ON CLUSTER emp_dept 3 TABLESPACE users 4 STORAGE (INITIAL 50K 5 NEXT 50K 6 MINEXTENTS 2 7 MAXEXTENTS 10 8 PCTINCREASE 33); Index created. SQL> SQL> begin 2 for i in 1..999 loop 3 insert into dept values (i,'D'||i,'L'||i,dbms_random.string('u',500)); 4 end loop; 5 commit; 6 end; 7 / PL/SQL procedure successfully completed. SQL> SQL> SQL> begin 2 for i in 1..500000 loop



Cluster created.

Practice 4-1: Using Different Access Paths (continued) 3 insert into emp values (i,dbms_random.string('u',15),dbms_random.string('u',9),i,sysdate,i, i,mod(i,999)); 4 end loop; 5 commit; 6 end; 7 / PL/SQL procedure successfully completed. SQL> SQL> exec dbms_stats.gather_schema_stats('SH');

SQL>

55) Execute the following query to confirm the performance enhancement of the previous query: select * from emp,dept where emp.deptno=dept.deptno and emp.deptno > 800;

What do you observe? a) The optimizer is able to use the cluster access path that makes the query execute faster. SQL> @ic_query SQL> set echo on SQL> SQL> set timing on SQL> set autotrace traceonly SQL> set linesize 200 SQL> SQL> select * from emp,dept where emp.deptno=dept.deptno and emp.deptno > 800; 99000 rows selected. Elapsed: 00:00:01.20 Execution Plan ---------------------------------------------------------Plan hash value: 593050162 --------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 19780 | 10M| 11515 (1)| 00:02:19 | | 1 | NESTED LOOPS | | 19780 | 10M| 11515 (1)| 00:02:19 | | 2 | TABLE ACCESS CLUSTER| DEPT | 199 | 99K| 167 (0)| 00:00:03 |




Practice 4-1: Using Different Access Paths (continued) |* 3 | INDEX RANGE SCAN | EMP_DEPT_INDEX | 1 | | 2 (0)| 00:00:01 | |* 4 | TABLE ACCESS CLUSTER| EMP | 99 | 5643 | 57 (0)| 00:00:01 | --------------------------------------------------------------------------------------Predicate Information (identified by operation id): ---------------------------------------------------


56) Execute the ic_cleanup.sql script to clean up your environment for this case. SQL> @ic_cleanup SQL> set echo on SQL> SQL> drop cluster emp_dept including tables; Cluster dropped. SQL> SQL> drop table emp purge; drop table emp purge * ERROR at line 1: ORA-00942: table or view does not exist SQL> drop table dept purge; drop table dept purge * ERROR at line 1: ORA-00942: table or view does not exist SQL> SQL>



3 - access("DEPT"."DEPTNO">800) 4 - filter("EMP"."DEPTNO">800 AND "EMP"."DEPTNO"="DEPT"."DEPTNO")

Practice 4-1: Using Different Access Paths (continued) 57) Case 16: Execute the iss_setup.sql script to set up your environment for this lab. SQL> @iss_setup SQL> set echo on SQL> SQL> create table t(c number, d number);

SQL> SQL> begin 2 for i in 1..10000 loop 3 insert into t values(1,i); 4 end loop; 5 end; 6 / PL/SQL procedure successfully completed. SQL> SQL> create index it on t(c,d); Index created. SQL>

58) Execute the following query: select count(*) from t where d=1;

What do you observe? a) The optimizer is not using the index and does a full table scan. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL>

@query20 set echo on set linesize 200 set timing on set autotrace on select count(*) from t where d=1;

COUNT(*) ---------1 Elapsed: 00:00:00.01 Execution Plan ---------------------------------------------------------Plan hash value: 2966233522 -------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |



Table created.

Practice 4-1: Using Different Access Paths (continued) -------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 13 | 7 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 13 | | | |* 2 | TABLE ACCESS FULL| T | 1 | 13 | 7 (0)| 00:00:01 | -------------------------------------------------------------------------Predicate Information (identified by operation id): ---------------------------------------------------

Note ----- dynamic sampling used for this statement


59) How would you improve the performance of a query, such as the one in the previous step? Implement your solution. a) Make sure you gather correctly the statistics for your table so that the index skip scan can be used. SQL> @iss_gather_stats SQL> set echo on SQL> SQL> execute dbms_stats.gather_table_stats('SH','T',cascade=>TRUE); PL/SQL procedure successfully completed. SQL>

60) Execute the following query: select count(*) from t where d=1;



2 - filter("D"=1)

Practice 4-1: Using Different Access Paths (continued) What do you observe? a) The optimizer now uses the index to perform an index skip scan. @query20 set echo on set linesize 200 set timing on set autotrace on select count(*) from t where d=1;

COUNT(*) ---------1 Elapsed: 00:00:00.00 Execution Plan ---------------------------------------------------------Plan hash value: 2609927160 -----------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -----------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 4 | 2 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 4 | | | |* 2 | INDEX SKIP SCAN| IT | 1 | 4 | 2 (0)| 00:00:01 | -----------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - access("D"=1) filter("D"=1)




SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL>




61) Compare the result of executing the previous query with the result you obtain when you execute the following query: select /*+ INDEX_FFS(t it) */ count(*) from t where d=1;

a) The optimizer uses a fast full index scan, but this is not better than the index skip scan. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL>

@query21 set echo on set linesize 200 set timing on set autotrace on select /*+ INDEX_FFS(t it) */ count(*) from t where d=1;

COUNT(*) ---------1 Elapsed: 00:00:00.00 Execution Plan ---------------------------------------------------------Plan hash value: 273610729 ----------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ----------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 4 | 9 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 4 | | | |* 2 | INDEX FAST FULL SCAN| IT | 1 | 4 | 9 (0)| 00:00:01 | ----------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - filter("D"=1)






62) Execute the iss_cleanup.sql script to clean up your environment for this case. SQL> @iss_cleanup SQL> set echo on SQL> SQL> drop table t purge; Table dropped. SQL> SQL>

63) Exit from your SQL*Plus session, and execute the ap_cleanup.sh script to clean up your environment for this lab. SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Access_Paths]$ ./ap_cleanup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Wed Apr 9 15:22:25 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> revoke dba from sh; Revoke succeeded.



Statistics ---------------------------------------------------------1 recursive calls 0 db block gets 31 consistent gets 0 physical reads 0 redo size 418 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 1 rows processed

Practice 4-1: Using Different Access Paths (continued) SQL> SQL> @sh_main sh example temp oracle /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/ /home/oracle/ v3 SQL> Rem SQL> Rem $Header: sh_main.sql 06-mar-2008.15:00:45 cbauwens Exp $ SQL> Rem

<<<<< CHANNELS DIMENSION >>>>> Dimension - display name, description and plural name Level - display name and description Hierarchy - display name and description - default calculation hierarchy - default display hierarchy Level Attributes - name, display name, description Drop dimension attributes prior to re-creation No attribute to drop Create dimension attributes and add their level attributes - Long Description created - Short Description created Classify entity descriptor use - Long Description - Short Description <<<<< FINAL PROCESSING >>>>> - Changes have been committed PL/SQL procedure successfully completed.

Commit complete.

gathering statistics ... PL/SQL procedure successfully completed.

PL/SQL procedure successfully completed. Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Access_Paths]$



....

Practice 4-2: Using the Result Cache In this practice, you explore the various possibilities of caching query results in the System Global Area (SGA). Perform the following steps to understand the use of Query Result Cache. 1) Change to the $HOME/solutions/Query_Result_Cache directory and execute the result_cache_setup.sh script. [oracle@edrsr33p1-orcl ~]$ cd $HOME/solutions/Query_Result_Cache [oracle@edrsr33p1-orcl Query_Result_Cache]$ ./result_cache_setup.sh



Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> SQL> SQL> drop user qrc cascade * ERROR at line 1: ORA-01918: user 'QRC' does not exist

SQL> SQL> 2 User created.

3

SQL> SQL> Grant succeeded. SQL> SQL> Connected. SQL> SQL> PL/SQL procedure successfully completed. SQL> SQL> drop table cachejfv purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> SQL> Table created. SQL> SQL> 1 row created. SQL> 1 row created. SQL> 2 rows created.



SQL*Plus: Release 11.1.0.6.0 - Production on Tue Mar 25 14:46:14 2008

Practice 4-2: Using the Result Cache (continued) SQL> 4 rows created. SQL> 8 rows created. SQL> 16 rows created. SQL> 32 rows created.

SQL> 128 rows created. SQL> 256 rows created. SQL> 512 rows created. SQL> 1024 rows created. SQL> 2048 rows created. SQL> 4096 rows created. SQL> 8192 rows created. SQL> 16384 rows created. SQL> 32768 rows created. SQL> 65536 rows created. SQL> 131072 rows created. SQL> 262144 rows created. SQL> 524288 rows created. SQL> 1048576 rows created.



SQL> 64 rows created.

Practice 4-2: Using the Result Cache (continued) SQL> SQL> 1 row created. SQL> SQL> Commit complete. SQL> SQL> System altered.

--------------------------------------------------------------

#!/bin/bash cd /home/oracle/solutions/Query_Result_Cache export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin sqlplus / as sysdba <


SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Query_Result_Cache]$

insert insert insert insert insert insert insert insert insert insert insert insert insert insert insert insert insert insert insert

into into into into into into into into into into into into into into into into into into into

cachejfv cachejfv cachejfv cachejfv cachejfv cachejfv cachejfv cachejfv cachejfv cachejfv cachejfv cachejfv cachejfv cachejfv cachejfv cachejfv cachejfv cachejfv cachejfv

select select select select select select select select select select select select select select select select select select select

* * * * * * * * * * * * * * * * * * *

from from from from from from from from from from from from from from from from from from from

cachejfv; cachejfv; cachejfv; cachejfv; cachejfv; cachejfv; cachejfv; cachejfv; cachejfv; cachejfv; cachejfv; cachejfv; cachejfv; cachejfv; cachejfv; cachejfv; cachejfv; cachejfv; cachejfv;

insert into cachejfv values('b'); commit; alter system flush buffer_cache; FIN!

2) Open a terminal window, invoke SQL*Plus, and connect as the qrc user. From now on, do not disconnect from this session. Determine the current content of the query cache using the following statement: select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1; What do you observe? a) Use the check_result_cache.sql script. Right now, the query cache should be empty. [oracle@edrsr33p1-orcl Query_Result_Cache]$ sqlplus qrc/qrc SQL*Plus: Release 11.1.0.6.0 - Production on Tue Mar 25 14:49:02 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> @check_result_cache SQL> SQL> select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1;



Practice 4-2: Using the Result Cache (continued)

Practice 4-2: Using the Result Cache (continued) no rows selected SQL> SQL>

-------------------------------------------------------------set echo on

3) Set timing on and execute the query as follows. You can use the query1.sql script. Note the time that it takes to execute. select /*+ result_cache q_name(Q1) */ count(*) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b'; SQL> set timing on SQL> @query1 COUNT(*) ---------1 Elapsed: 00:00:02.46 SQL> -------------------------------------------------------------select /*+ result_cache q_name(Q1) */ count(*) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b';

4) Determine the execution plan of the previous query by using the explain_query1.sql script. What do you observe? a) Because of the result_cache hint, the result of the query is computed using the result cache. SQL> @explain_query1 SQL> set echo on SQL> SQL> explain plan for 2 select /*+ result_cache q_name(Q1) */ count(*) 3 from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 4 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b';



select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1;

Practice 4-2: Using the Result Cache (continued) Explained.

PLAN_TABLE_OUTPUT ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Plan hash value: 2531260445 --------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 1764 | 7316P (1)|999:59:59 | | 1 | RESULT CACHE | b7rh5vw33py4ug4n8xaav6525g | | | | | | 2 | SORT AGGREGATE | | 1 | 1764 | | | | 3 | MERGE JOIN CARTESIAN | | 294P| 15E| 7316P (1)|999:59:59 | | 4 | MERGE JOIN CARTESIAN | | 941T| 1264P| 23P (1)|999:59:59 | | 5 | MERGE JOIN CARTESIAN | | 3007G| 3446T| 74T (1)|999:59:59 | | 6 | MERGE JOIN CARTESIAN | | 9606M| 9018G| 238G (1)|999:59:59 | | 7 | MERGE JOIN CARTESIAN | | 30M| 21G| 761M (1)|999:59:59 | | 8 | MERGE JOIN CARTESIAN| | 98011 | 47M| 2432K (1)| 08:06:26 | |* 9 | TABLE ACCESS FULL | CACHEJFV | 313 | 78876 | 7748 (1)| 00:01:33 | | 10 | BUFFER SORT | | 313 | 78876 | 2424K (1)| 08:04:53 | |* 11 | TABLE ACCESS FULL | CACHEJFV | 313 | 78876 | 7746 (1)| 00:01:33 | | 12 | BUFFER SORT | | 313 | 78876 | 761M (1)|999:59:59 | |* 13 | TABLE ACCESS FULL | CACHEJFV | 313 | 78876 | 7746 (1)| 00:01:33 | | 14 | BUFFER SORT | | 313 | 78876 | 238G (1)|999:59:59 | |* 15 | TABLE ACCESS FULL | CACHEJFV | 313 | 78876 | 7746 (1)| 00:01:33 | | 16 | BUFFER SORT | | 313 | 78876 | 74T (1)|999:59:59 |



Elapsed: 00:00:00.05 SQL> SQL> set linesize 180 SQL> set pagesize 200 SQL> SQL> select plan_table_output from table(dbms_xplan.display('plan_table',null,'ALL'));

Practice 4-2: Using the Result Cache (continued) |* 17 | TABLE ACCESS FULL | CACHEJFV | 313 | 78876 | 7746 (1)| 00:01:33 | | 18 | BUFFER SORT | | 313 | 78876 | 23P (1)|999:59:59 | |* 19 | TABLE ACCESS FULL | CACHEJFV | 313 | 78876 | 7746 (1)| 00:01:33 | | 20 | BUFFER SORT | | 313 | 78876 | 7316P (1)|999:59:59 | |* 21 | TABLE ACCESS FULL | CACHEJFV | 313 | 78876 | 7746 (1)| 00:01:33 | ---------------------------------------------------------------------------------------------------------

1 9 11 13 15 17 19 21

-

SEL$1 SEL$1 SEL$1 SEL$1 SEL$1 SEL$1 SEL$1 SEL$1

/ / / / / / /

C7@SEL$1 C6@SEL$1 C5@SEL$1 C4@SEL$1 C3@SEL$1 C2@SEL$1 C1@SEL$1

Predicate Information (identified by operation id): --------------------------------------------------9 11 13 15 17 19 21

-

filter("C7"."C"='b') filter("C6"."C"='b') filter("C5"."C"='b') filter("C4"."C"='b') filter("C3"."C"='b') filter("C2"."C"='b') filter("C1"."C"='b')

Column Projection Information (identified by operation id): ----------------------------------------------------------1 - COUNT(*)[22] 2 - (#keys=0) COUNT(*)[22] 3 - (#keys=0) "C7"."C"[VARCHAR2,500], "C6"."C"[VARCHAR2,500], "C5"."C"[VARCHAR2,500], "C4"."C"[VARCHAR2,500], "C3"."C"[VARCHAR2,500], "C2"."C"[VARCHAR2,500], "C1"."C"[VARCHAR2,500] 4 - (#keys=0) "C7"."C"[VARCHAR2,500], "C6"."C"[VARCHAR2,500], "C5"."C"[VARCHAR2,500], "C4"."C"[VARCHAR2,500], "C3"."C"[VARCHAR2,500], "C2"."C"[VARCHAR2,500] 5 - (#keys=0) "C7"."C"[VARCHAR2,500], "C6"."C"[VARCHAR2,500], "C5"."C"[VARCHAR2,500], "C4"."C"[VARCHAR2,500], "C3"."C"[VARCHAR2,500] 6 - (#keys=0) "C7"."C"[VARCHAR2,500], "C6"."C"[VARCHAR2,500], "C5"."C"[VARCHAR2,500], "C4"."C"[VARCHAR2,500] 7 - (#keys=0) "C7"."C"[VARCHAR2,500], "C6"."C"[VARCHAR2,500], "C5"."C"[VARCHAR2,500]



Query Block Name / Object Alias (identified by operation id): -------------------------------------------------------------

Practice 4-2: Using the Result Cache (continued) -

(#keys=0) "C7"."C"[VARCHAR2,500], "C6"."C"[VARCHAR2,500] "C7"."C"[VARCHAR2,500] (#keys=0) "C6"."C"[VARCHAR2,500] "C6"."C"[VARCHAR2,500] (#keys=0) "C5"."C"[VARCHAR2,500] "C5"."C"[VARCHAR2,500] (#keys=0) "C4"."C"[VARCHAR2,500] "C4"."C"[VARCHAR2,500] (#keys=0) "C3"."C"[VARCHAR2,500] "C3"."C"[VARCHAR2,500] (#keys=0) "C2"."C"[VARCHAR2,500] "C2"."C"[VARCHAR2,500] (#keys=0) "C1"."C"[VARCHAR2,500] "C1"."C"[VARCHAR2,500]

Result Cache Information (identified by operation id): -----------------------------------------------------1 - column-count=1; dependencies=(QRC.CACHEJFV); attributes=(single-row); parameters=(nls); name="select /*+ result_cache q_name(Q1) */ count(*) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cac"

Note ----- dynamic sampling used for this statement 89 rows selected. Elapsed: 00:00:00.03 SQL> -------------------------------------------------------------set echo on explain plan for select /*+ result_cache q_name(Q1) */ count(*) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b'; set linesize 180 set pagesize 200 select plan_table_output from table(dbms_xplan.display('plan_table',null,'ALL'));

5) Determine the current content of the query cache by using the check_result_cache.sql script. What do you observe? a) You can now see the result of your query cached. Oracle Database 11g: SQL Tuning Workshop A - 128


8 9 10 11 12 13 14 15 16 17 18 19 20 21


TYPE STATUS NAME OBJECT_NO ROW_COUNT ---------- --------- ------------------------------------------------------------------------------------------------------------------------------ ---------- ---------ROW_SIZE_AVG -----------Dependency Published QRC.CACHEJFV 71474 0 0 Result 0 1

Published select /*+ result_cache q_name(Q1) */ count(*)

from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cac 5

Elapsed: 00:00:00.00 SQL> Elapsed: 00:00:00.00 SQL> -------------------------------------------------------------set echo on set long 2000 select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1;

6) Flush the buffer cache of your instance and rerun the query executed in step 3. What do you observe? a) The execution time for the query is now almost instantaneous. SQL> alter system flush buffer_cache; System altered. Elapsed: 00:00:00.05 SQL> @query1 SQL> select /*+ result_cache q_name(Q1) */ count(*) 2 from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7



SQL> @check_result_cache SQL> set echo on SQL> SQL> set long 2000 SQL> SQL> select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1;

Practice 4-2: Using the Result Cache (continued) 3 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b'; COUNT(*) ---------1 Elapsed: 00:00:00.00 SQL>

select /*+ result_cache q_name(Q1) */ count(*) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b';

7) Insert a new row into the CACHEJFV table using the following statement: insert into cachejfv values('c');

What do you observe? a) The corresponding result cache entry is automatically invalidated. SQL> insert into cachejfv values('c'); 1 row created. Elapsed: 00:00:00.00 SQL> commit; Commit complete. Elapsed: 00:00:00.00 SQL> @check_result_cache SQL> set echo on SQL> SQL> set long 2000 SQL> SQL> select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1; TYPE STATUS NAME OBJECT_NO ROW_COUNT ---------- --------- ------------------------------------------------------------------------------------------------------------------------------ ---------- ---------ROW_SIZE_AVG -----------Dependency Published QRC.CACHEJFV 71474 0 0 Result 0 1

Invalid

select /*+ result_cache q_name(Q1) */ count(*)



--------------------------------------------------------------

Practice 4-2: Using the Result Cache (continued) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cac 5

Elapsed: 00:00:00.00 SQL> -------------------------------------------------------------set echo on

select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1;

8) Execute your query from step 3 and step 6 again and check the result cache. What do you observe? a) Again, it takes some time to execute the query. The result cache shows that a new entry has been added for the new result. SQL> @query1 SQL> select /*+ result_cache q_name(Q1) */ count(*) 2 from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 3 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b'; COUNT(*) ---------1 Elapsed: 00:00:02.33 SQL> SQL> @check_result_cache SQL> set echo on SQL> SQL> set long 2000 SQL> SQL> select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1; TYPE STATUS NAME OBJECT_NO ROW_COUNT ---------- --------- ------------------------------------------------------------------------------------------------------------------------------ ---------- ---------ROW_SIZE_AVG -----------Dependency Published QRC.CACHEJFV 71474 0 0



set long 2000

Practice 4-2: Using the Result Cache (continued) Result 0 1

Invalid


from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cac 5 Result 0 1



-------------------------------------------------------------select /*+ result_cache q_name(Q1) */ count(*) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b';

set echo on set long 2000 select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1;

9) Generate a detailed result cache memory report. SQL> set serveroutput on SQL> EXEC DBMS_RESULT_CACHE.MEMORY_REPORT(detailed=>true); R e s u l t C a c h e M e m o r y R e p o r t [Parameters] Block Size = 1K bytes Maximum Cache Size = 2080K bytes (2080 blocks) Maximum Result Size = 104K bytes (104 blocks) [Memory] Total Memory = 116008 bytes [0.035% of the Shared Pool] ... Fixed Memory = 5132 bytes [0.002% of the Shared Pool] ....... Cache Mgr = 108 bytes ....... Memory Mgr = 124 bytes ....... Bloom Fltr = 2K bytes ....... State Objs = 2852 bytes ... Dynamic Memory = 110876 bytes [0.033% of the Shared Pool] ....... Overhead = 78108 bytes ........... Hash Table = 32K bytes (4K buckets) ........... Chunk Ptrs = 12K bytes (3K slots) ........... Chunk Maps = 12K bytes ........... Miscellaneous = 20764 bytes ....... Cache Memory = 32K bytes (32 blocks)




Practice 4-2: Using the Result Cache (continued) ........... Unused Memory = 29 blocks ........... Used Memory = 3 blocks ............... Dependencies = 1 blocks (1 count) ............... Results = 2 blocks ................... SQL = 1 blocks (1 count) ................... Invalid = 1 blocks (1 count) PL/SQL procedure successfully completed. Elapsed: 00:00:00.12 SQL>

10) Execute your query from step 3 and step 6 again. What do you observe? SQL> @query1 SQL> select /*+ result_cache q_name(Q1) */ count(*) 2 from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 3 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b'; COUNT(*) ---------1 Elapsed: 00:00:00.01 SQL> -------------------------------------------------------------select /*+ result_cache q_name(Q1) */ count(*) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b'; 11) Ensure that you bypass the result cache before performing the next step. SQL> SQL> exec DBMS_RESULT_CACHE.BYPASS(bypass_mode=>true); PL/SQL procedure successfully completed. Elapsed: 00:00:00.01 SQL>

12) Execute your query again. What do you observe? a) The query again takes longer to execute because it no longer uses the result cache. SQL> @query1 SQL> select /*+ result_cache q_name(Q1) */ count(*) 2 from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 3 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b';



a) The query again uses the result that was previously cached.

Practice 4-2: Using the Result Cache (continued) COUNT(*) ---------1 Elapsed: 00:00:02.34 SQL> --------------------------------------------------------------

13) Ensure that you no longer bypass the result cache and check that your query uses it again. SQL> exec DBMS_RESULT_CACHE.BYPASS(bypass_mode=>false); PL/SQL procedure successfully completed. Elapsed: 00:00:00.01 SQL> @query1 SQL> select /*+ result_cache q_name(Q1) */ count(*) 2 from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 3 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b'; COUNT(*) ---------1 Elapsed: 00:00:00.00 SQL> SQL> -------------------------------------------------------------select /*+ result_cache q_name(Q1) */ count(*) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b';

14) Execute the following query by using the query2.sql script: select count(*) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b';




select /*+ result_cache q_name(Q1) */ count(*) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b';

Practice 4-2: Using the Result Cache (continued) a) Although the query is the same as the one used in step 3, it is not recognized as cached because it does not contain the hint. So its execution time is long again. SQL> @query2 SQL> select count(*) 2 from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 3 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b';

Elapsed: 00:00:02.41 SQL> -------------------------------------------------------------select count(*) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b';

15) How would you force the previous query to use the cached result without using hints? Use the force_query2.sql script and then verify that you successfully used the cached result. Finally, undo your change. SQL> @force_query2 SQL> set echo on SQL> SQL> show parameter result_cache_mode NAME TYPE VALUE ------------------------------------ ----------- ----------------------------result_cache_mode string MANUAL SQL> SQL> select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1; TYPE STATUS NAME OBJECT_NO ROW_COUNT ---------- --------- ------------------------------------------------------------------------------------------------------------------------------ ---------- ---------ROW_SIZE_AVG -----------Dependency Published QRC.CACHEJFV 71474 0 0 Result 0 1

Invalid




COUNT(*) ---------1

Practice 4-2: Using the Result Cache (continued) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cac 5 Result 0 1



Session altered. Elapsed: 00:00:00.04 SQL> SQL> explain plan for 2 select count(*) 3 from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 4 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b'; Explained. Elapsed: 00:00:00.05 SQL> SQL> set linesize 180 SQL> set pagesize 200 SQL> SQL> select plan_table_output from table(dbms_xplan.display('plan_table',null,'ALL')); PLAN_TABLE_OUTPUT ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Plan hash value: 2531260445 --------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 1764 | 7316P (1)|999:59:59 | | 1 | RESULT CACHE | b7rh5vw33py4ug4n8xaav6525g | | | | | | 2 | SORT AGGREGATE | | 1 | 1764 | | | | 3 | MERGE JOIN CARTESIAN | | 294P| 15E| 7316P (1)|999:59:59 |



Elapsed: 00:00:00.00 SQL> SQL> alter session set result_cache_mode=force;

| 4 | MERGE JOIN CARTESIAN | | 941T| 1264P| 23P (1)|999:59:59 | | 5 | MERGE JOIN CARTESIAN | | 3007G| 3446T| 74T (1)|999:59:59 | | 6 | MERGE JOIN CARTESIAN | | 9606M| 9018G| 238G (1)|999:59:59 | | 7 | MERGE JOIN CARTESIAN | | 30M| 21G| 761M (1)|999:59:59 | | 8 | MERGE JOIN CARTESIAN| | 98011 | 47M| 2432K (1)| 08:06:26 | |* 9 | TABLE ACCESS FULL | CACHEJFV | 313 | 78876 | 7748 (1)| 00:01:33 | | 10 | BUFFER SORT | | 313 | 78876 | 2424K (1)| 08:04:53 | |* 11 | TABLE ACCESS FULL | CACHEJFV | 313 | 78876 | 7746 (1)| 00:01:33 | | 12 | BUFFER SORT | | 313 | 78876 | 761M (1)|999:59:59 | |* 13 | TABLE ACCESS FULL | CACHEJFV | 313 | 78876 | 7746 (1)| 00:01:33 | | 14 | BUFFER SORT | | 313 | 78876 | 238G (1)|999:59:59 | |* 15 | TABLE ACCESS FULL | CACHEJFV | 313 | 78876 | 7746 (1)| 00:01:33 | | 16 | BUFFER SORT | | 313 | 78876 | 74T (1)|999:59:59 | |* 17 | TABLE ACCESS FULL | CACHEJFV | 313 | 78876 | 7746 (1)| 00:01:33 | | 18 | BUFFER SORT | | 313 | 78876 | 23P (1)|999:59:59 | |* 19 | TABLE ACCESS FULL | CACHEJFV | 313 | 78876 | 7746 (1)| 00:01:33 | | 20 | BUFFER SORT | | 313 | 78876 | 7316P (1)|999:59:59 | |* 21 | TABLE ACCESS FULL | CACHEJFV | 313 | 78876 | 7746 (1)| 00:01:33 | --------------------------------------------------------------------------------------------------------Query Block Name / Object Alias (identified by operation id): ------------------------------------------------------------1 9 11 13 15 17 19 21

-

SEL$1 SEL$1 SEL$1 SEL$1 SEL$1 SEL$1 SEL$1 SEL$1

/ / / / / / /

C7@SEL$1 C6@SEL$1 C5@SEL$1 C4@SEL$1 C3@SEL$1 C2@SEL$1 C1@SEL$1

Predicate Information (identified by operation id): --------------------------------------------------9 - filter("C7"."C"='b') 11 - filter("C6"."C"='b') 13 - filter("C5"."C"='b')




Practice 4-2: Using the Result Cache (continued) 15 17 19 21

-

filter("C4"."C"='b') filter("C3"."C"='b') filter("C2"."C"='b') filter("C1"."C"='b')

1 - COUNT(*)[22] 2 - (#keys=0) COUNT(*)[22] 3 - (#keys=0) "C7"."C"[VARCHAR2,500], "C6"."C"[VARCHAR2,500], "C5"."C"[VARCHAR2,500], "C4"."C"[VARCHAR2,500], "C3"."C"[VARCHAR2,500], "C2"."C"[VARCHAR2,500], "C1"."C"[VARCHAR2,500] 4 - (#keys=0) "C7"."C"[VARCHAR2,500], "C6"."C"[VARCHAR2,500], "C5"."C"[VARCHAR2,500], "C4"."C"[VARCHAR2,500], "C3"."C"[VARCHAR2,500], "C2"."C"[VARCHAR2,500] 5 - (#keys=0) "C7"."C"[VARCHAR2,500], "C6"."C"[VARCHAR2,500], "C5"."C"[VARCHAR2,500], "C4"."C"[VARCHAR2,500], "C3"."C"[VARCHAR2,500] 6 - (#keys=0) "C7"."C"[VARCHAR2,500], "C6"."C"[VARCHAR2,500], "C5"."C"[VARCHAR2,500], "C4"."C"[VARCHAR2,500] 7 - (#keys=0) "C7"."C"[VARCHAR2,500], "C6"."C"[VARCHAR2,500], "C5"."C"[VARCHAR2,500] 8 - (#keys=0) "C7"."C"[VARCHAR2,500], "C6"."C"[VARCHAR2,500] 9 - "C7"."C"[VARCHAR2,500] 10 - (#keys=0) "C6"."C"[VARCHAR2,500] 11 - "C6"."C"[VARCHAR2,500] 12 - (#keys=0) "C5"."C"[VARCHAR2,500] 13 - "C5"."C"[VARCHAR2,500] 14 - (#keys=0) "C4"."C"[VARCHAR2,500] 15 - "C4"."C"[VARCHAR2,500] 16 - (#keys=0) "C3"."C"[VARCHAR2,500] 17 - "C3"."C"[VARCHAR2,500] 18 - (#keys=0) "C2"."C"[VARCHAR2,500] 19 - "C2"."C"[VARCHAR2,500] 20 - (#keys=0) "C1"."C"[VARCHAR2,500] 21 - "C1"."C"[VARCHAR2,500] Result Cache Information (identified by operation id): -----------------------------------------------------1 - column-count=1; dependencies=(QRC.CACHEJFV); attributes=(single-row); parameters=(nls); name="select count(*) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 where c1.c='b' and c2."

Note ----- dynamic sampling used for this statement 89 rows selected.



Column Projection Information (identified by operation id): -----------------------------------------------------------

Practice 4-2: Using the Result Cache (continued) Elapsed: 00:00:00.07 SQL> SQL> select count(*) 2 from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 3 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b';

Elapsed: 00:00:00.04 SQL> SQL> select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1; TYPE STATUS NAME OBJECT_NO ROW_COUNT ---------- --------- ------------------------------------------------------------------------------------------------------------------------------ ---------- ---------ROW_SIZE_AVG -----------Dependency Published QRC.CACHEJFV 71474 0 0 Result 0 1

Invalid


from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cac 5 Result 0 1



Elapsed: 00:00:00.00 SQL> SQL> alter session set result_cache_mode=manual; Session altered. Elapsed: 00:00:00.00 SQL> SQL> -------------------------------------------------------------set echo on show parameter result_cache_mode



COUNT(*) ---------1

Practice 4-2: Using the Result Cache (continued) select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1; alter session set result_cache_mode=force; explain plan for select count(*) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b';

select plan_table_output from table(dbms_xplan.display('plan_table',null,'ALL')); select count(*) from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 where c1.c='b' and c2.c='b' and c3.c='b' and c4.c='b' and c5.c='b' and c6.c='b' and c7.c='b'; select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1; alter session set result_cache_mode=manual;

16) Clear the result cache. Query V$RESULT_CACHE_OBJECTS to verify the clear operation. SQL> exec dbms_result_cache.flush; PL/SQL procedure successfully completed. Elapsed: 00:00:00.01 SQL> select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1; no rows selected Elapsed: 00:00:00.00 SQL>

17) Create a PL/SQL function that uses the result cache by running the cre_func.sql script. SQL> SQL> 2 3 4 5 6 7

@cre_func create or replace function CACHEJFV_COUNT(v varchar2) return number result_cache relies_on (cachejfv) is cnt number; begin select count(*) into cnt



set linesize 180 set pagesize 200

Practice 4-2: Using the Result Cache (continued) 8 from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 9 where c1.c=v and c2.c=v and c3.c=v and c4.c=v and c5.c=v and c6.c=v and c7.c=v; 10 return cnt; 11 end; 12 / Function created. Elapsed: 00:00:00.15 SQL>

create or replace function CACHEJFV_COUNT(v varchar2) return number result_cache relies_on (cachejfv) is cnt number; begin select count(*) into cnt from cachejfv c1,cachejfv c2,cachejfv c3,cachejfv c4,cachejfv c5,cachejfv c6, cachejfv c7 where c1.c=v and c2.c=v and c3.c=v and c4.c=v and c5.c=v and c6.c=v and c7.c=v; return cnt; end; /

18) Determine what is in the result cache by querying V$RESULT_CACHE_OBJECTS. SQL> select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1; no rows selected Elapsed: 00:00:00.00 SQL>

19) Call the new function with ‘b’ as its argument. What do you observe? a) It takes a long time to execute because the result is not cached yet. After executing the function, the function’s result for the ‘b’ argument is cached. SQL> select cachejfv_count('b') from dual; CACHEJFV_COUNT('B') ------------------1 Elapsed: 00:00:01.56 SQL> SQL> select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1;



--------------------------------------------------------------

Practice 4-2: Using the Result Cache (continued) TYPE STATUS NAME OBJECT_NO ROW_COUNT ---------- --------- ------------------------------------------------------------------------------------------------------------------------------ ---------- ---------ROW_SIZE_AVG -----------Dependency Published QRC.CACHEJFV_COUNT 71475 0 0

Result Published "QRC"."CACHEJFV_COUNT"::8."CACHEJFV_COUNT"#8440831613f0f5d3 #1 0 1 4

Elapsed: 00:00:00.00 SQL> SQL>

20) Call the new function with ‘b’ as its argument again. What do you observe? a) This time the function executes almost instantaneously. SQL> select cachejfv_count('b') from dual; CACHEJFV_COUNT('B') ------------------1 Elapsed: 00:00:00.00 SQL>

21) Call the new function with ‘c’ as its argument again. What do you observe? a) Again it takes a long time to execute the function because of the new value for the argument. After execution, the second result is cached. SQL> select cachejfv_count('c') from dual; CACHEJFV_COUNT('C') ------------------1 Elapsed: 00:00:04.15 SQL> select type,status,name,object_no,row_count,row_size_avg from v$result_cache_objects order by 1; TYPE STATUS NAME OBJECT_NO ROW_COUNT ---------- --------- ------------------------------------------------------------------------------------------------------------------------------ ---------- ----------



Dependency Published QRC.CACHEJFV 71474 0 0

Practice 4-2: Using the Result Cache (continued) ROW_SIZE_AVG -----------Dependency Published QRC.CACHEJFV_COUNT 71475 0 0 Dependency Published QRC.CACHEJFV 71474 0 0


Elapsed: 00:00:00.01 SQL> SQL> SQL> select cachejfv_count('c') from dual; CACHEJFV_COUNT('C') ------------------1 Elapsed: 00:00:00.00 SQL>







Practice 5-1: Extracting Execution Plans In this practice, you use various methods to extract the execution plan used by the optimizer to execute a query. Note that all scripts needed for this lab can be found in your $HOME/solutions/Explain_Plan directory. 1) Connected as the oracle user from a terminal session, execute the ep_setup.sh script. This script creates a new user called EP and a table called TEST used throughout this lab. [oracle@edrsr33p1-orcl Explain_Plan]$ ./ep_setup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Wed Apr 2 20:11:45 2008 All rights reserved.

Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> drop user ep cascade; drop user ep cascade * ERROR at line 1: ORA-01918: user 'EP' does not exist

SQL> SQL> create user ep identified by ep default tablespace users temporary tablespace temp; User created. SQL> SQL> grant connect, resource, dba to ep; Grant succeeded. SQL> SQL> connect ep/ep Connected. SQL> SQL> drop table test purge; drop table test purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> SQL> create table test(c number, d varchar2(500)); Table created.




Practice 5-1: Extracting Execution Plans (continued) SQL> SQL> begin 2 for i in 1..20000 loop 3 insert into test values(1,'aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa'); 4 end loop; 5 commit; 6 end; 7 /

SQL> SQL> create index test_c_indx on test(c); Index created. SQL> SQL> exec dbms_stats.gather_schema_stats('EP'); PL/SQL procedure successfully completed. SQL> SQL> alter system flush shared_pool; System altered. SQL> SQL> alter system flush buffer_cache; System altered. SQL> SQL> set echo off Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Explain_Plan]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Explain_Plan export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin




Practice 5-1: Extracting Execution Plans (continued) sqlplus / as sysdba @ep_setup.sql -------------------------------------------------------------set echo on drop user ep cascade; create user ep identified by ep default tablespace users temporary tablespace temp; grant connect, resource, dba to ep;

drop table test purge; create table test(c number, d varchar2(500)); begin for i in 1..20000 loop insert into test values(1,'aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa'); end loop; commit; end; / create index test_c_indx on test(c); exec dbms_stats.gather_schema_stats('EP'); alter system flush shared_pool; alter system flush buffer_cache; set echo off set term off select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1; exit;

2) From the same terminal session (referred to as session 1 in the rest of this lab), be ready to execute the ep_session_issue.sh script. Enter the command, but do not execute it yet. Session 1: ---------[oracle@edrsr33p1-orcl Explain_Plan]$ ./ep_session_issue.sh --------------------------------------------------------------



connect ep/ep

Practice 5-1: Extracting Execution Plans (continued) #!/bin/bash cd /home/oracle/solutions/Explain_Plan export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus ep/ep @ep_session_issue.sql

set echo off set termout off alter session set optimizer_mode=rule; set termout on set echo on set timing on select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1; exit;

3) From a second terminal session (referred to as session 2 in the rest of this lab), connect as the oracle user. After this, connect to a SQL*Plus session as the SYS user. From that SQL*Plus session, be ready to use SQL Monitoring to monitor the execution plan used by session 1. You can execute the ep_monitoring.sql script for that purpose. Enter the command, but do not execute it yet. Note: Ensure that you understand the coordination between both sessions by pre-reading steps 4 and 5 before you continue. Session 2: ---------[oracle@edrsr33p1-orcl Explain_Plan]$ sqlplus / as sysdba SQL*Plus: Release 11.1.0.6.0 - Production on Wed Apr 2 20:12:28 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> @ep_monitor



--------------------------------------------------------------

Practice 5-1: Extracting Execution Plans (continued) -------------------------------------------------------------set set set set set

echo on long 10000000 longchunksize 10000000 linesize 200 pagesize 1000

exec dbms_lock.sleep(8);

4) After you are ready in both the sessions, press [Enter] in session 1 to start the execution of the ep_session_issue.sh script. Note: Do not wait. Proceed with the next step immediately. Session 1: ---------[oracle@edrsr33p1-orcl Explain_Plan]$ ./ep_session_issue.sh SQL*Plus: Release 11.1.0.6.0 - Production on Wed Apr 2 20:12:47 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> set timing on SQL> SQL> select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1;

5) In session 2, enter return to start the execution of the ep_monitor.sql script. After the execution, enter “/” and go back to your SQL*Plus session as many times as necessary until session 1 is done with its execution. What do you observe? a) You can see that session 1 uses NESTED LOOPS on top of two INDEX RANGE SCANS to execute the query. It takes approximately 47 seconds to execute session 1’s query. The time depends on your environment. The big advantage of SQL Monitoring is that you can clearly see which steps in the execution plan take most of the resources. In this case, you clearly see that you do only one scan of the index, and that for each row returned, you execute another index scan to probe. This is not really efficient. Also there is no costs information for this monitored plan.



select dbms_sqltune.report_sql_monitor(sql_id=>'dkz7v96ym42c6',report_level =>'ALL') from dual;

Practice 5-1: Extracting Execution Plans (continued) Session 2: ---------SQL> SQL> SQL> SQL> SQL> SQL> SQL>

@ep_monitor set long 10000000 set longchunksize 10000000 set linesize 200 set pagesize 1000 exec dbms_lock.sleep(8);

SQL> SQL> select dbms_sqltune.report_sql_monitor(sql_id=>'dkz7v96ym42c6',report_level =>'ALL') from dual; DBMS_SQLTUNE.REPORT_SQL_MONITOR(SQL_ID=>'DKZ7V96YM42C6',SESSION_ID=> :SESSID,REPORT_LEVEL=>'ALL') -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL Monitoring Report SQL Text --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1 --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Global Information Status Instance ID Session ID SQL ID SQL Execution ID Plan Hash Value Execution Started First Refresh Time Last Refresh Time

: : : : : : : : :

EXECUTING 1 138 dkz7v96ym42c6 16777222 1643938535 04/02/2008 20:12:46 04/02/2008 20:12:54 04/02/2008 20:12:56

----------------------------------------| Elapsed | Cpu | Other | Buffer | | Time(s) | Time(s) | Waits(s) | Gets | ----------------------------------------| 8.10 | 8.09 | 0.01 | 134K | -----------------------------------------

SQL Plan Monitoring Details ==================================================================== =================================================================




| Id | Operation | Name | Rows | Cost | Time | Start | Starts | Rows | Activity | Activity Detail | | | | | (Estim) | | Active(s) | Active | | (Actual) | (percent) | (sample #) | ==================================================================== ================================================================= | 0 | SELECT STATEMENT | | | | | | 1 | | | | | 1 | SORT AGGREGATE | | | | 1 | +6 | 1 | 0 | 12.50 | Cpu (1) | | -> 2 | NESTED LOOPS | | | | 3 | +8 | 1 | 79096K | | | | -> 3 | INDEX RANGE SCAN | TEST_C_INDX | | | 3 | +8 | 1 | 3954 | | | | -> 4 | INDEX RANGE SCAN | TEST_C_INDX | | | 9 | +2 | 3955 | 79096K | 87.50 | Cpu (7) | ==================================================================== =================================================================

SQL> SQL> / DBMS_SQLTUNE.REPORT_SQL_MONITOR(SQL_ID=>'DKZ7V96YM42C6',SESSION_ID=> :SESSID,REPORT_LEVEL=>'ALL') -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL Monitoring Report SQL Text --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1 --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Global Information Status Instance ID Session ID SQL ID SQL Execution ID Plan Hash Value Execution Started First Refresh Time Last Refresh Time

: : : : : : : : :


----------------------------------------| Elapsed | Cpu | Other | Buffer | | Time(s) | Time(s) | Waits(s) | Gets | ----------------------------------------| 10 | 10 | 0.01 | 167K | -----------------------------------------



Practice 5-1: Extracting Execution Plans (continued)

SQL Plan Monitoring Details ==================================================================== ================================================================= | Id | Operation | Name | Rows | Cost | Time | Start | Starts | Rows | Activity | Activity Detail | | | | | (Estim) | | Active(s) | Active | | (Actual) | (percent) | (sample #) | ==================================================================== ================================================================= | 0 | SELECT STATEMENT | | | | | | 1 | | | | | 1 | SORT AGGREGATE | | | | 1 | +6 | 1 | 0 | 10.00 | Cpu (1) | | -> 2 | NESTED LOOPS | | | | 5 | +8 | 1 | 96151K | | | | -> 3 | INDEX RANGE SCAN | TEST_C_INDX | | | 5 | +8 | 1 | 4807 | | | | -> 4 | INDEX RANGE SCAN | TEST_C_INDX | | | 11 | +2 | 4808 | 96151K | 90.00 | Cpu (9) | ==================================================================== =================================================================

SQL> / DBMS_SQLTUNE.REPORT_SQL_MONITOR(SQL_ID=>'DKZ7V96YM42C6',SESSION_ID=> :SESSID,REPORT_LEVEL=>'ALL') -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL Monitoring Report SQL Text --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1 --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Global Information Status Instance ID Session ID SQL ID SQL Execution ID Plan Hash Value Execution Started First Refresh Time Last Refresh Time

: : : : : : : : :


----------------------------------------| Elapsed | Cpu | Other | Buffer |





SQL Plan Monitoring Details ==================================================================== ================================================================= | Id | Operation | Name | Rows | Cost | Time | Start | Starts | Rows | Activity | Activity Detail | | | | | (Estim) | | Active(s) | Active | | (Actual) | (percent) | (sample #) | ==================================================================== ================================================================= | 0 | SELECT STATEMENT | | | | | | 1 | | | | | 1 | SORT AGGREGATE | | | | 1 | +6 | 1 | 0 | 8.33 | Cpu (1) | | -> 2 | NESTED LOOPS | | | | 7 | +8 | 1 | 113M | | | | -> 3 | INDEX RANGE SCAN | TEST_C_INDX | | | 7 | +8 | 1 | 5664 | | | | -> 4 | INDEX RANGE SCAN | TEST_C_INDX | | | 13 | +2 | 5665 | 113M | 91.67 | Cpu (11) | ==================================================================== =================================================================

SQL> / DBMS_SQLTUNE.REPORT_SQL_MONITOR(SQL_ID=>'DKZ7V96YM42C6',SESSION_ID=> :SESSID,REPORT_LEVEL=>'ALL') -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL Monitoring Report SQL Text --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1 --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Global Information Status Instance ID Session ID SQL ID SQL Execution ID Plan Hash Value Execution Started First Refresh Time

: : : : : : : :

EXECUTING 1 138 dkz7v96ym42c6 16777222 1643938535 04/02/2008 20:12:46 04/02/2008 20:12:54



| Time(s) | Time(s) | Waits(s) | Gets | ----------------------------------------| 12 | 12 | 0.01 | 201K | -----------------------------------------

Practice 5-1: Extracting Execution Plans (continued) Last Refresh Time

:

04/02/2008 20:13:08


SQL> / DBMS_SQLTUNE.REPORT_SQL_MONITOR(SQL_ID=>'DKZ7V96YM42C6',SESSION_ID=> :SESSID,REPORT_LEVEL=>'ALL') -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL Monitoring Report SQL Text --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1 --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Global Information Status Instance ID Session ID SQL ID

: : : :

EXECUTING 1 138 dkz7v96ym42c6




Practice 5-1: Extracting Execution Plans (continued) SQL Execution ID Plan Hash Value Execution Started First Refresh Time Last Refresh Time

: : : : :

16777222 1643938535 04/02/2008 20:12:46 04/02/2008 20:12:54 04/02/2008 20:13:17


SQL> / DBMS_SQLTUNE.REPORT_SQL_MONITOR(SQL_ID=>'DKZ7V96YM42C6',SESSION_ID=> :SESSID,REPORT_LEVEL=>'ALL') -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL Monitoring Report SQL Text --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1 --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Global Information




Practice 5-1: Extracting Execution Plans (continued) : : : : : : : : :




SQL> / DBMS_SQLTUNE.REPORT_SQL_MONITOR(SQL_ID=>'DKZ7V96YM42C6',SESSION_ID=> :SESSID,REPORT_LEVEL=>'ALL') -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL Monitoring Report SQL Text --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1



Status Instance ID Session ID SQL ID SQL Execution ID Plan Hash Value Execution Started First Refresh Time Last Refresh Time

Practice 5-1: Extracting Execution Plans (continued) --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: : : : : : : : :

DONE (ALL ROWS) 1 138 dkz7v96ym42c6 16777222 1643938535 04/02/2008 20:12:46 04/02/2008 20:12:54 04/02/2008 20:13:34

------------------------------------------------| Elapsed | Cpu | Other | Fetch | Buffer | | Time(s) | Time(s) | Waits(s) | Calls | Gets | ------------------------------------------------| 46 | 46 | 0.06 | 1 | 760K | -------------------------------------------------

SQL Plan Monitoring Details ==================================================================== =============================================================== | Id | Operation | Name | Rows | Cost | Time | Start | Starts | Rows | Activity | Activity Detail | | | | | (Estim) | | Active(s) | Active | | (Actual) | (percent) | (sample #) | ==================================================================== =============================================================== | 0 | SELECT STATEMENT | | | | 1 | +48 | 1 | 1 | | | | 1 | SORT AGGREGATE | | | | 43 | +6 | 1 | 1 | 4.35 | Cpu (2) | | 2 | NESTED LOOPS | | | | 41 | +8 | 1 | 400M | | | | 3 | INDEX RANGE SCAN | TEST_C_INDX | | | 41 | +8 | 1 | 20000 | | | | 4 | INDEX RANGE SCAN | TEST_C_INDX | | | 47 | +2 | 20000 | 400M | 95.65 | Cpu (44) | ==================================================================== ===============================================================

SQL>

6) After approximately 47 seconds (depending on your environment), you should see the following output in your session 1: Session 1: ----------



Global Information Status Instance ID Session ID SQL ID SQL Execution ID Plan Hash Value Execution Started First Refresh Time Last Refresh Time

Practice 5-1: Extracting Execution Plans (continued) … COUNT(*) ---------400000000

[oracle@edrsr33p1-orcl Explain_Plan]$

7) From session 1, connect as the EP user in the SQL*Plus session. Session 1: ---------[oracle@edrsr33p1-orcl Explain_Plan]$ sqlplus ep/ep SQL*Plus: Release 11.1.0.6.0 - Production on Wed Apr 2 20:14:03 2008 Copyright (c) 1982, 2007, Oracle.



8) Use PLAN_TABLE to determine the execution plan of the query that was executed in step 4. What do you observe? select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1;

a) This time the execution plan uses a hash join on top of two index fast full scans. Session 1: ---------SQL> @ep_explain SQL> SQL> set linesize 200 pagesize 1000 SQL> SQL> explain plan for 2 select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1; Explained. SQL> SQL> select * from table(dbms_xplan.display);



Elapsed: 00:00:47.21 SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options


------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 6 | 2131 (99)| 00:00:22 | | 1 | SORT AGGREGATE | | 1 | 6 | | | |* 2 | HASH JOIN | | 400M| 2288M| 2131 (99)| 00:00:22 | |* 3 | INDEX FAST FULL SCAN| TEST_C_INDX | 20000 | 60000 | 13 (0)| 00:00:01 | |* 4 | INDEX FAST FULL SCAN| TEST_C_INDX | 20000 | 60000 | 13 (0)| 00:00:01 | ------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - access("T1"."C"="T2"."C") 3 - filter("T1"."C"=1) 4 - filter("T2"."C"=1) 18 rows selected. SQL> -------------------------------------------------------------set echo on set linesize 200 pagesize 1000 explain plan for select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1; select * from table(dbms_xplan.display);

9) Now, you want to monitor the previous execution plan to compare it with the one generated in step 4. In addition, you want to make sure you use the correct plan this time. So, in your session 1, start autotrace, and be ready to execute the following query. Do not execute it yet as you need to start SQL Monitoring in your session 2: select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1;



PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Plan hash value: 3253233075

Practice 5-1: Extracting Execution Plans (continued) Session 1: ---------SQL> set autotrace on SQL> @ep_execute

10) From your session 2, be ready to execute your SQL Monitoring command again. Do not execute it yet though.

SQL> @ep_monitor -------------------------------------------------------------set set set set set

echo on long 10000000 longchunksize 10000000 linesize 200 pagesize 1000

exec dbms_lock.sleep(8); select dbms_sqltune.report_sql_monitor(sql_id=>'dkz7v96ym42c6',report_level =>'ALL') from dual;

11) Start the execution of your query from session 1 by pressing [Enter]. Note: Move to next stepwithout waiting. Session 1: ---------SQL> @ep_execute SQL> set echo on SQL> SQL> set timing on SQL> SQL> select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1; -------------------------------------------------------------set echo on set timing on select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1;



Session 2: ----------

Practice 5-1: Extracting Execution Plans (continued) 12) From your session 2, start monitoring your query by pressing the return key. After the query is executed, enter “/” and go back to your SQL*Plus session as many times as necessary until session 1 is done with its execution. What do you observe? a) You can see that the optimizer uses a hash join on top of two index fast full scans. Looking at the various reports, you can clearly see how the optimizer processes a hash join by reading the driving index in memory first. This operation is quick. Though you cannot see it run, it is already done the first time you can look at it. Then the probe in performed on the index again. This operation takes more time. Also note that cost information is provided in the execution plan.

SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL>

@ep_monitor set echo on set long 10000000 set longchunksize 10000000 set linesize 200 set pagesize 1000 exec dbms_lock.sleep(8);

PL/SQL procedure successfully completed. SQL> SQL> select dbms_sqltune.report_sql_monitor(sql_id=>'dkz7v96ym42c6',report_level =>'ALL') from dual; DBMS_SQLTUNE.REPORT_SQL_MONITOR(SQL_ID=>'DKZ7V96YM42C6',SESSION_ID=> :SESSID,REPORT_LEVEL=>'ALL') -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL Monitoring Report SQL Text --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1 --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Global Information Status Instance ID Session ID SQL ID SQL Execution ID Plan Hash Value Execution Started First Refresh Time

: : : : : : : :

EXECUTING 1 124 dkz7v96ym42c6 16777223 3253233075 04/02/2008 20:14:41 04/02/2008 20:14:49



Session 2: ----------

Practice 5-1: Extracting Execution Plans (continued) Last Refresh Time

:

04/02/2008 20:14:49

SQL Plan Monitoring Details ==================================================================== ==================================================================== ========== | Id | Operation | Name | Rows | Cost | Time | Start | Starts | Rows | Memory | Activity | Activity Detail | | | | | (Estim) | | Active(s) | Active | | (Actual) | | (percent) | (sample #) | ==================================================================== ==================================================================== ========== | 0 | SELECT STATEMENT | | | 2131 | | | 1 | | | | | | 1 | SORT AGGREGATE | | 1 | | 8 | +0 | 1 | 0 | | 25.00 | Cpu (2) | | -> 2 | HASH JOIN | | 400M | 2131 | 8 | +1 | 1 | 113M | 1138K | 75.00 | Cpu (6) | | -> 3 | INDEX FAST FULL SCAN | TEST_C_INDX | 20000 | 13 | 1 | +8 | 1 | 20000 | | | | | -> 4 | INDEX FAST FULL SCAN | TEST_C_INDX | 20000 | 13 | 1 | +8 | 1 | 5632 | | | | ==================================================================== ==================================================================== ==========

SQL> SQL> / DBMS_SQLTUNE.REPORT_SQL_MONITOR(SQL_ID=>'DKZ7V96YM42C6',SESSION_ID=> :SESSID,REPORT_LEVEL=>'ALL') -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL Monitoring Report SQL Text ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------



----------------------------------------| Elapsed | Cpu | Other | Buffer | | Time(s) | Time(s) | Waits(s) | Gets | ----------------------------------------| 6.29 | 6.29 | 0.00 | 8 | -----------------------------------------

Practice 5-1: Extracting Execution Plans (continued) select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

: : : : : : : : :


----------------------------------------| Elapsed | Cpu | Other | Buffer | | Time(s) | Time(s) | Waits(s) | Gets | ----------------------------------------| 7.86 | 7.86 | 0.00 | 10 | -----------------------------------------

SQL Plan Monitoring Details ==================================================================== ==================================================================== ========== | Id | Operation | Name | Rows | Cost | Time | Start | Starts | Rows | Memory | Activity | Activity Detail | | | | | (Estim) | | Active(s) | Active | | (Actual) | | (percent) | (sample #) | ==================================================================== ==================================================================== ========== | 0 | SELECT STATEMENT | | | 2131 | | | 1 | | | | | | 1 | SORT AGGREGATE | | 1 | | 8 | +0 | 1 | 0 | | 20.00 | Cpu (2) | | -> 2 | HASH JOIN | | 400M | 2131 | 10 | +1 | 1 | 133M | 1138K | 80.00 | Cpu (8) | | 3 | INDEX FAST FULL SCAN | TEST_C_INDX | 20000 | 13 | 1 | +8 | 1 | 20000 | | | | | -> 4 | INDEX FAST FULL SCAN | TEST_C_INDX | 20000 | 13 | 3 | +8 | 1 | 6656 | | | | ==================================================================== ==================================================================== ==========



Global Information Status Instance ID Session ID SQL ID SQL Execution ID Plan Hash Value Execution Started First Refresh Time Last Refresh Time

Practice 5-1: Extracting Execution Plans (continued) SQL> /

SQL Text --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1 --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Global Information Status Instance ID Session ID SQL ID SQL Execution ID Plan Hash Value Execution Started First Refresh Time Last Refresh Time

: : : : : : : : :


----------------------------------------| Elapsed | Cpu | Other | Buffer | | Time(s) | Time(s) | Waits(s) | Gets | ----------------------------------------| 12 | 12 | 0.00 | 15 | -----------------------------------------

SQL Plan Monitoring Details ==================================================================== ==================================================================== ========== | Id | Operation | Name | Rows | Cost | Time | Start | Starts | Rows | Memory | Activity | Activity Detail | | | | | (Estim) | | Active(s) | Active | | (Actual) | | (percent) | (sample #) | ==================================================================== ==================================================================== ========== | 0 | SELECT STATEMENT | | | 2131 | | | 1 | | | | | | 1 | SORT AGGREGATE | | 1 | | 8 | +0 | 1 | 0 | | 14.29 | Cpu (2) |



DBMS_SQLTUNE.REPORT_SQL_MONITOR(SQL_ID=>'DKZ7V96YM42C6',SESSION_ID=> :SESSID,REPORT_LEVEL=>'ALL') -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL Monitoring Report

Practice 5-1: Extracting Execution Plans (continued) | -> 2 | HASH JOIN | | 400M | 2131 | 14 | +1 | 1 | 184M | 1138K | 85.71 | Cpu (12) | | 3 | INDEX FAST FULL SCAN | TEST_C_INDX | 20000 | 13 | 1 | +8 | 1 | 20000 | | | | | -> 4 | INDEX FAST FULL SCAN | TEST_C_INDX | 20000 | 13 | 7 | +8 | 1 | 9216 | | | | ==================================================================== ==================================================================== ==========

DBMS_SQLTUNE.REPORT_SQL_MONITOR(SQL_ID=>'DKZ7V96YM42C6',SESSION_ID=> :SESSID,REPORT_LEVEL=>'ALL') -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL Monitoring Report SQL Text --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1 --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Global Information Status Instance ID Session ID SQL ID SQL Execution ID Plan Hash Value Execution Started First Refresh Time Last Refresh Time

: : : : : : : : :


----------------------------------------| Elapsed | Cpu | Other | Buffer | | Time(s) | Time(s) | Waits(s) | Gets | ----------------------------------------| 22 | 22 | 0.01 | 28 | -----------------------------------------

SQL Plan Monitoring Details ==================================================================== ==================================================================== ==========



SQL> /

| Id | Operation | Name | Rows | Cost | Time | Start | Starts | Rows | Memory | Activity | Activity Detail | | | | | (Estim) | | Active(s) | Active | | (Actual) | | (percent) | (sample #) | ==================================================================== ==================================================================== ========== | 0 | SELECT STATEMENT | | | 2131 | | | 1 | | | | | | 1 | SORT AGGREGATE | | 1 | | 8 | +0 | 1 | 0 | | 8.33 | Cpu (2) | | -> 2 | HASH JOIN | | 400M | 2131 | 24 | +1 | 1 | 317M | 1138K | 91.67 | Cpu (22) | | 3 | INDEX FAST FULL SCAN | TEST_C_INDX | 20000 | 13 | 1 | +8 | 1 | 20000 | | | | | -> 4 | INDEX FAST FULL SCAN | TEST_C_INDX | 20000 | 13 | 17 | +8 | 1 | 15872 | | | | ==================================================================== ==================================================================== ==========

SQL> / DBMS_SQLTUNE.REPORT_SQL_MONITOR(SQL_ID=>'DKZ7V96YM42C6',SESSION_ID=> :SESSID,REPORT_LEVEL=>'ALL') -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL Monitoring Report SQL Text --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1 --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Global Information Status Instance ID Session ID SQL ID SQL Execution ID Plan Hash Value Execution Started First Refresh Time Last Refresh Time

: : : : : : : : :

DONE (ALL ROWS) 1 124 dkz7v96ym42c6 16777223 3253233075 04/02/2008 20:14:41 04/02/2008 20:14:49 04/02/2008 20:15:11





SQL Plan Monitoring Details ==================================================================== ==================================================================== ======== | Id | Operation | Name | Rows | Cost | Time | Start | Starts | Rows | Memory | Activity | Activity Detail | | | | | (Estim) | | Active(s) | Active | | (Actual) | (Max) | (percent) | (sample #) | ==================================================================== ==================================================================== ======== | 0 | SELECT STATEMENT | | | 2131 | 1 | +30 | 1 | 1 | | | | | 1 | SORT AGGREGATE | | 1 | | 31 | +0 | 1 | 1 | | 10.00 | Cpu (3) | | 2 | HASH JOIN | | 400M | 2131 | 30 | +1 | 1 | 400M | 1138K | 90.00 | Cpu (27) | | 3 | INDEX FAST FULL SCAN | TEST_C_INDX | 20000 | 13 | 1 | +8 | 1 | 20000 | | | | | 4 | INDEX FAST FULL SCAN | TEST_C_INDX | 20000 | 13 | 23 | +8 | 1 | 20000 | | | | ==================================================================== ==================================================================== ========

SQL>

13) When your query is executed, what do you observe in your session 1? a) Session 1 also reports the same execution plan as the one you observed in session 2. Session 1: ---------… COUNT(*)



------------------------------------------------| Elapsed | Cpu | Other | Fetch | Buffer | | Time(s) | Time(s) | Waits(s) | Calls | Gets | ------------------------------------------------| 28 | 28 | 0.01 | 1 | 37 | -------------------------------------------------

Practice 5-1: Extracting Execution Plans (continued) ---------400000000 Elapsed: 00:00:30.70

------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 6 | 2131 (99)| 00:00:22 | | 1 | SORT AGGREGATE | | 1 | 6 | | | |* 2 | HASH JOIN | | 400M| 2288M| 2131 (99)| 00:00:22 | |* 3 | INDEX FAST FULL SCAN| TEST_C_INDX | 20000 | 60000 | 13 (0)| 00:00:01 | |* 4 | INDEX FAST FULL SCAN| TEST_C_INDX | 20000 | 60000 | 13 (0)| 00:00:01 | ------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - access("T1"."C"="T2"."C") 3 - filter("T1"."C"=1) 4 - filter("T2"."C"=1)


14) In session 1, disable autotrace. Session 1: ----------




Practice 5-1: Extracting Execution Plans (continued) SQL> set autotrace off SQL>

15) From your session 1, how can you ensure that you gather all execution plan statistics for the following query without changing any session parameters? Implement your solution. select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1; Session 1: ---------@ep_execute_with_all set echo on set timing on select /*+ gather_plan_statistics */ count(*) from test t1, t2 where t1.c=t2.c and t1.c=1;

COUNT(*) ---------400000000 Elapsed: 00:00:59.95 SQL>

16) From your session 1, retrieve all execution plans corresponding to all the queries you executed since the beginning of this lab. What is your conclusion? a) The easiest way to find out all the plans is to look at the content of the SGA using the dbms_xplan.display_cursor function. First, you must determine the SQL_Ids used to represent your queries. You essentially have two queries, and one that has two children. You should now understand what happened at step 4. The fact that there was no cost information is probably due to the use of the rulebased optimizer instead of the cost-based one. Session 1: ---------SQL> @ep_retrieve_all_plans SQL> set echo on SQL> SQL> set linesize 200 pagesize 1000 SQL> SQL> col sql_text format a50 SQL> SQL> select sql_id,plan_hash_value,sql_text from v$sql where sql_text like '%from test t1, test t2%'; SQL_ID PLAN_HASH_VALUE SQL_TEXT ------------- --------------- -------------------------------------------------



SQL> SQL> SQL> SQL> SQL> SQL> test

Practice 5-1: Extracting Execution Plans (continued) dkz7v96ym42c6 where t1.c=t

3253233075 select count(*) from test t1, test t2 2.c and t1.c=1

dkz7v96ym42c6 where t1.c=t

1643938535 select count(*) from test t1, test t2 2.c and t1.c=1

8w580dd6ncgqw count(*) from

3253233075 select /*+ gather_plan_statistics */ test t1, test t2 where t1.c=t2.c and

t1.c=1 3253233075 explain plan for select count(*) from t t2 where t1.c=t2.c and t1.c=1 dd09kf5dnp1gt from v$sql

903671040 select sql_id,plan_hash_value,sql_text where sql_text like '%from test t1,

test t2%' 32fqwuk16uf23 3253233075 EXPLAIN PLAN SET STATEMENT_ID='PLUS2140495' FOR se lect count(*) from test t1, test t2 where t1.c=t2. c and t1.c=1

6 rows selected. Elapsed: 00:00:00.02 SQL> SQL> select * from table(dbms_xplan.display_cursor('dkz7v96ym42c6',null,'TYPICAL')); PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID dkz7v96ym42c6, child number 0 ------------------------------------select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1 Plan hash value: 3253233075 ------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | | | 2131 (100)| | | 1 | SORT AGGREGATE | | 1 | 6 | | |



0w0va2d7hhtxa test t1, tes

Practice 5-1: Extracting Execution Plans (continued) |* 2 | HASH JOIN | | 400M| 2288M| 2131 (99)| 00:00:22 | |* 3 | INDEX FAST FULL SCAN| TEST_C_INDX | 20000 | 60000 | 13 (0)| 00:00:01 | |* 4 | INDEX FAST FULL SCAN| TEST_C_INDX | 20000 | 60000 | 13 (0)| 00:00:01 | ------------------------------------------------------------------------------------Predicate Information (identified by operation id): ---------------------------------------------------

SQL_ID dkz7v96ym42c6, child number 1 ------------------------------------select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1 Plan hash value: 1643938535 -----------------------------------------| Id | Operation | Name | -----------------------------------------| 0 | SELECT STATEMENT | | | 1 | SORT AGGREGATE | | | 2 | NESTED LOOPS | | |* 3 | INDEX RANGE SCAN| TEST_C_INDX | |* 4 | INDEX RANGE SCAN| TEST_C_INDX | -----------------------------------------Predicate Information (identified by operation id): --------------------------------------------------3 - access("T1"."C"=1) 4 - access("T1"."C"="T2"."C") Note ----- rule based optimizer used (consider using cbo)

49 rows selected. Elapsed: 00:00:00.04 SQL> SQL> select * from table(dbms_xplan.display_cursor('8w580dd6ncgqw',null,'ADVANCED ALLSTATS LAST')); PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID 8w580dd6ncgqw, child number 0 -------------------------------------



2 - access("T1"."C"="T2"."C") 3 - filter("T1"."C"=1) 4 - filter("T2"."C"=1)

Practice 5-1: Extracting Execution Plans (continued) select /*+ gather_plan_statistics */ count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1

--------------------------------------------------------------------------------------------------------------------------------------------------------| Id | Operation | Name | Starts | E-Rows |EBytes| Cost (%CPU)| E-Time | A-Rows | A-Time | Buffers | OMem | 1Mem | Used-Mem | --------------------------------------------------------------------------------------------------------------------------------------------------------| 1 | SORT AGGREGATE | | 1 | 1 | 6 | | | 1 |00:00:59.94 | 90 | | | | |* 2 | HASH JOIN | | 1 | 400M| 2288M| 2131 (99)| 00:00:22 | 400M|00:00:00.01 | 90 | 1155K| 1155K| 1115K (0)| |* 3 | INDEX FAST FULL SCAN| TEST_C_INDX | 1 | 20000 | 60000 | 13 (0)| 00:00:01 | 20000 |00:00:00.02 | 45 | | | | |* 4 | INDEX FAST FULL SCAN| TEST_C_INDX | 1 | 20000 | 60000 | 13 (0)| 00:00:01 | 20000 |00:00:00.16 | 45 | | | | --------------------------------------------------------------------------------------------------------------------------------------------------------Query Block Name / Object Alias (identified by operation id): ------------------------------------------------------------1 - SEL$1 3 - SEL$1 / T1@SEL$1 4 - SEL$1 / T2@SEL$1 Outline Data ------------/*+ BEGIN_OUTLINE_DATA IGNORE_OPTIM_EMBEDDED_HINTS OPTIMIZER_FEATURES_ENABLE('11.1.0.6') DB_VERSION('11.1.0.6') ALL_ROWS OUTLINE_LEAF(@"SEL$1") INDEX_FFS(@"SEL$1" "T1"@"SEL$1" ("TEST"."C")) INDEX_FFS(@"SEL$1" "T2"@"SEL$1" ("TEST"."C")) LEADING(@"SEL$1" "T1"@"SEL$1" "T2"@"SEL$1") USE_HASH(@"SEL$1" "T2"@"SEL$1") END_OUTLINE_DATA */ Predicate Information (identified by operation id): ---------------------------------------------------




Practice 5-1: Extracting Execution Plans (continued) 2 - access("T1"."C"="T2"."C") 3 - filter("T1"."C"=1) 4 - filter("T2"."C"=1) Column Projection Information (identified by operation id): ----------------------------------------------------------1 2 3 4

-

(#keys=0) COUNT(*)[22] (#keys=1) "T1"."C"[NUMBER,22] "T2"."C"[NUMBER,22]

Elapsed: 00:00:00.12 SQL> -------------------------------------------------------------set echo on set linesize 200 pagesize 1000 col sql_text format a50 select sql_id,plan_hash_value,sql_text from v$sql where sql_text like '%from test t1, test t2%'; select * from table(dbms_xplan.display_cursor('dkz7v96ym42c6',null,'TYPICAL')); select * from table(dbms_xplan.display_cursor('8w580dd6ncgqw',null,'ADVANCED ALLSTATS LAST'));

17) From session 1, try to retrieve your execution plans from the Automatic Workload Repository. What happens and why? a) You can use the previously found SQL_Ids to search through the DBA_HIST_SQLTEXT view. You should see that right now, none of your queries were stored in the AWR. Session 1: ---------SQL> SQL> SQL> SQL> SQL> SQL> 2

@ep_retrieve_awr set echo on set linesize 200 SELECT SQL_ID, SQL_TEXT FROM dba_hist_sqltext WHERE SQL_ID in ('dkz7v96ym42c6','8w580dd6ncgqw');

no rows selected



55 rows selected.

Practice 5-1: Extracting Execution Plans (continued) SQL> Elapsed: 00:00:00.01 SQL> -------------------------------------------------------------set echo on set linesize 200

18) How can you ensure that you retrieve your queries from the Automatic Workload Repository? Implement your solution. a) You must flush the SGA information to the AWR. You can use DBMS_WORKLOAD_REPOSITORY.CREATE_SNAPSHOT for this purpose. Session 1: ---------SQL> @ep_save_awr SQL> set echo on SQL> SQL> EXEC DBMS_WORKLOAD_REPOSITORY.CREATE_SNAPSHOT('ALL'); PL/SQL procedure successfully completed. Elapsed: 00:00:02.27 SQL> -------------------------------------------------------------set echo on EXEC DBMS_WORKLOAD_REPOSITORY.CREATE_SNAPSHOT('ALL');

19) Verify that your solution works. Session 1: ---------SQL> SQL> SQL> SQL> SQL> SQL> 2 3

@ep_show_awr set echo on set linesize 200 pagesize 1000 SELECT PLAN_TABLE_OUTPUT FROM TABLE (DBMS_XPLAN.DISPLAY_AWR('dkz7v96ym42c6'));



SELECT SQL_ID, SQL_TEXT FROM dba_hist_sqltext WHERE SQL_ID in ('dkz7v96ym42c6','8w580dd6ncgqw');

Practice 5-1: Extracting Execution Plans (continued) PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID dkz7v96ym42c6 -------------------select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1

-----------------------------------------| Id | Operation | Name | -----------------------------------------| 0 | SELECT STATEMENT | | | 1 | SORT AGGREGATE | | | 2 | NESTED LOOPS | | | 3 | INDEX RANGE SCAN| TEST_C_INDX | | 4 | INDEX RANGE SCAN| TEST_C_INDX | -----------------------------------------Note ----- rule based optimizer used (consider using cbo) SQL_ID dkz7v96ym42c6 -------------------select count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1 Plan hash value: 3253233075 ------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | | | 543 (100)| | | 1 | SORT AGGREGATE | | 1 | 6 | | | | 2 | HASH JOIN | | 100M| 572M| 543 (98)| 00:00:06 | | 3 | INDEX FAST FULL SCAN| TEST_C_INDX | 10000 | 30000 | 8 (0)| 00:00:01 | | 4 | INDEX FAST FULL SCAN| TEST_C_INDX | 10000 | 30000 | 8 (0)| 00:00:01 | -------------------------------------------------------------------------------------

36 rows selected. Elapsed: 00:00:00.04 SQL> SQL> SELECT PLAN_TABLE_OUTPUT 2 FROM




Practice 5-1: Extracting Execution Plans (continued) 3 TABLE (DBMS_XPLAN.DISPLAY_AWR('8w580dd6ncgqw',null,null,'TYPICAL ALLSTATS LAST')); PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID 8w580dd6ncgqw -------------------select /*+ gather_plan_statistics */ count(*) from test t1, test t2 where t1.c=t2.c and t1.c=1

-------------------------------------------------------------------------------------| Id | Operation | Name | E-Rows |E-Bytes| Cost (%CPU)| E-Time | -------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | | | 2131 (100)| | | 1 | SORT AGGREGATE | | 1 | 6 | | | | 2 | HASH JOIN | | 400M| 2288M| 2131 (99)| 00:00:22 | | 3 | INDEX FAST FULL SCAN| TEST_C_INDX | 20000 | 60000 | 13 (0)| 00:00:01 | | 4 | INDEX FAST FULL SCAN| TEST_C_INDX | 20000 | 60000 | 13 (0)| 00:00:01 | -------------------------------------------------------------------------------------Note ----- Warning: basic plan statistics not available. These are only collected when: * hint 'gather_plan_statistics' is used for the statement or * parameter 'statistics_level' is set to 'ALL', at session or system level

23 rows selected. Elapsed: 00:00:00.02 SQL> -------------------------------------------------------------set echo on set linesize 200 pagesize 1000 SELECT PLAN_TABLE_OUTPUT FROM TABLE (DBMS_XPLAN.DISPLAY_AWR('dkz7v96ym42c6'));




Practice 5-1: Extracting Execution Plans (continued) SELECT PLAN_TABLE_OUTPUT FROM TABLE (DBMS_XPLAN.DISPLAY_AWR('8w580dd6ncgqw',null,null,'TYPICAL ALLSTATS LAST'));

20) Exit from both SQL*Plus sessions, and clean up your environment by executing the ep_cleanup.sh script from one of your terminal sessions.

SQL> exit Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Explain_Plan]$ ./ep_cleanup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Wed Apr 2 20:19:37 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> drop user ep cascade; User dropped. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Explain_Plan]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Explain_Plan export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1



Session 1: ----------

Practice 5-1: Extracting Execution Plans (continued) export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @ep_cleanup.sql -------------------------------------------------------------set echo on drop user ep cascade;

Do not forget to exit from your session 2: Session 2: ---------SQL> exit Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Explain_Plan]$



exit;




Practice 6-1: Star Schema Tuning In this practice, you optimize a query to use star transformation and access the benefits of using this optimizer technique. 1) From a terminal session, connected as the oracle user, execute the setup_star_schema_lab.sh script located in your /home/oracle/solutions/Star_Schema_Tuning directory. [oracle@edrsr33p1-orcl Star_Schema_Tuning]$ ./setup_star_schema_lab.sh



Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> SQL> SQL> Grant succeeded. SQL> SQL> User altered. SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Star_Schema_Tuning]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Star_Schema_Tuning export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin sqlplus / as sysdba <


SQL*Plus: Release 11.1.0.6.0 - Production on Fri Mar 21 00:17:20 2008

Practice 6-1: Star Schema Tuning (continued) alter user sh identified by sh account unlock; FIN!

SELECT ch.channel_class, c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold) sales_amount FROM sales s, times t, customers c, channels ch WHERE s.time_id = t.time_id AND s.cust_id = c.cust_id AND s.channel_id = ch.channel_id AND c.cust_state_province = 'CA' AND ch.channel_desc in ('Internet','Catalog') AND t.calendar_quarter_desc IN ('1999-01','1999-02','2000-03','2000-04') GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc;

What are your conclusions? a) As you can see in the output of the execution plan, this query seems to use a large number of bytes to access the SALES table. Basically, the optimizer performs a full scan of this table. This might not be the best way to handle it. [oracle@edrsr33p1-orcl Star_Schema_Tuning]$ sqlplus sh/sh SQL*Plus: Release 11.1.0.6.0 - Production on Fri Mar 21 00:31:10 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> @first_run SQL> SQL> alter system flush shared_pool; System altered. SQL> alter system flush buffer_cache; System altered. SQL> SQL> set pagesize 200 SQL> set linesize 250



2) From the same terminal window, start a SQL*Plus session connected as the SH user and do not disconnect from it until this lab finishes. Before executing the following SQL statement, ensure that you flush both the shared pool and the buffer cache to avoid caching issues as much as possible. After this, analyze the execution of the following query (You can use the query.sql script.):

Practice 6-1: Star Schema Tuning (continued) SQL> set timing on SQL> set autotrace on SQL> SELECT ch.channel_class, c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold) sales_amount FROM sales s, times t, customers c, channels ch WHERE s.time_id = t.time_id AND s.cust_id = c.cust_id AND s.channel_id = ch.channel_id AND c.cust_state_province = 'CA' AND ch.channel_desc in ('Internet','Catalog') AND t.calendar_quarter_desc IN ('1999-01','1999-02','2000-03','2000-04') GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc;

CHANNEL_CLASS SALES_AMOUNT ----------------------Indirect 987.3 Indirect … Montara Indirect 412.83

CUST_CITY

CALENDA

------------------------------ ------- -------Quartzhill

1999-01

Arbuckle

1999-02

1999-02 Quartzhill

1618.01 1999-02

41 rows selected. Elapsed: 00:00:00.68 Execution Plan ---------------------------------------------------------Plan hash value: 1647000731 ------------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | Pstart| Pstop | ------------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1144 | 96096 | 935 (4)| 00:00:12 | | | | 1 | HASH GROUP BY | | 1144 | 96096 | 935 (4)| 00:00:12 | | | |* 2 | HASH JOIN | | 6231 | 511K| 934 (3)| 00:00:12 | | | |* 3 | TABLE ACCESS FULL | CHANNELS | 2 | 42 | 3 (0)| 00:00:01 | | | |* 4 | HASH JOIN | | 12462 | 766K| 930 (3)| 00:00:12 | | | | 5 | PART JOIN FILTER CREATE | :BF0000 | 365 | 5840 | 18 (0)| 00:00:01 | | | |* 6 | TABLE ACCESS FULL | TIMES | 365 | 5840 | 18 (0)| 00:00:01 | | | |* 7 | HASH JOIN | | 49822 | 2286K| 911 (3)| 00:00:11 | | | |* 8 | TABLE ACCESS FULL | CUSTOMERS | 383 | 9958 | 406 (1)| 00:00:05 | | | | 9 | PARTITION RANGE JOIN-FILTER| | 918K| 18M| 498 (4)| 00:00:06 |:BF0000|:BF0000| | 10 | TABLE ACCESS FULL | SALES | 918K| 18M| 498 (4)| 00:00:06 |:BF0000|:BF0000| ------------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 3 4 6

-

access("S"."CHANNEL_ID"="CH"."CHANNEL_ID") filter("CH"."CHANNEL_DESC"='Catalog' OR "CH"."CHANNEL_DESC"='Internet') access("S"."TIME_ID"="T"."TIME_ID") filter("T"."CALENDAR_QUARTER_DESC"='1999-01' OR "T"."CALENDAR_QUARTER_DESC"='1999-02' OR "T"."CALENDAR_QUARTER_DESC"='2000-03' OR "T"."CALENDAR_QUARTER_DESC"='2000-04') 7 - access("S"."CUST_ID"="C"."CUST_ID") 8 - filter("C"."CUST_STATE_PROVINCE"='CA')

Statistics ---------------------------------------------------------16783 recursive calls 0 db block gets 5491 consistent gets 2021 physical reads 0 redo size 1888 bytes sent via SQL*Net to client 442 bytes received via SQL*Net from client



SQL> 2 3 4 5 6 7 8 9 10

Practice 6-1: Star Schema Tuning (continued) 4 141 0 41

SQL*Net roundtrips to/from client sorts (memory) sorts (disk) rows processed

SQL> SQL> -------------------------------------------------------------set echo on

set set set set

pagesize 200 linesize 250 timing on autotrace on

SELECT ch.channel_class, c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold) sales_amount FROM sales s, times t, customers c, channels ch WHERE s.time_id = t.time_id AND s.cust_id = c.cust_id AND s.channel_id = ch.channel_id AND c.cust_state_province = 'CA' AND ch.channel_desc in ('Internet','Catalog') AND t.calendar_quarter_desc IN ('1999-01','1999-02','200003','2000-04') GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc;

3) Without modifying the SH schema, how can you improve the execution plan for the query mentioned in step 2? Verify your solution and explain why it is probably a better solution. a) Enable star transformation in your session. In this step, you do not want to use a temporary table for the star transformation. Looking at the previous execution plan, the optimizer estimates the data that is to be manipulated in megabytes. Using the star transformation as follows, the estimation is now expressed in kilobytes. That is why this new execution plan is probably a much better alternative. However, note that this time the CUSTOMERS table is accessed using full scan twice. If the table is larger, the impact is significant. SQL> @second_run SQL> set echo on SQL> SQL> SQL> alter system flush shared_pool; System altered. Elapsed: 00:00:00.10 SQL> alter system flush buffer_cache;



alter system flush shared_pool; alter system flush buffer_cache;

Practice 6-1: Star Schema Tuning (continued) System altered. Elapsed: 00:00:00.20 SQL> SQL> set pagesize 200 SQL> set linesize 250 SQL> set timing on SQL> set autotrace on SQL> SQL> SQL> ALTER SESSION SET star_transformation_enabled=TEMP_DISABLE;

Elapsed: 00:00:00.00 SQL> SQL> SQL> SELECT ch.channel_class, c.cust_city, t.calendar_quarter_desc, 2 SUM(s.amount_sold) sales_amount 3 FROM sales s, times t, customers c, channels ch 4 WHERE s.time_id = t.time_id 5 AND s.cust_id = c.cust_id 6 AND s.channel_id = ch.channel_id 7 AND c.cust_state_province = 'CA' 8 AND ch.channel_desc in ('Internet','Catalog') 9 AND t.calendar_quarter_desc IN ('1999-01','1999-02','200003','2000-04') 10 GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc; CHANNEL_CLASS SALES_AMOUNT ----------------------Indirect 13227.99 Indirect 1319 Indirect 7.27 … Indirect Indirect 1618.01 Indirect 412.83 Indirect 3058.27 Indirect 3263.93

CUST_CITY

CALENDA

------------------------------ ------- -------San Francisco

2000-04

Montara

2000-04

Cloverdale

2000-04

Pala Montara

2000-03 1999-02

Quartzhill

1999-02

San Francisco

1999-01

Pala

1999-01

41 rows selected. Elapsed: 00:00:00.33 Execution Plan ---------------------------------------------------------Plan hash value: 2525768690



Session altered.

--------------------------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | Pstart| Pstop | --------------------------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 3 | 252 | 983 (1)| 00:00:12 | | | | 1 | HASH GROUP BY | | 3 | 252 | 983 (1)| 00:00:12 | | | |* 2 | HASH JOIN | | 3 | 252 | 982 (1)| 00:00:12 | | | |* 3 | HASH JOIN | | 7 | 441 | 978 (1)| 00:00:12 | | | |* 4 | HASH JOIN | | 27 | 1269 | 960 (1)| 00:00:12 | | | |* 5 | TABLE ACCESS FULL | CUSTOMERS | 383 | 9958 | 406 (1)| 00:00:05 | | | | 6 | PARTITION RANGE SUBQUERY | | 507 | 10647 | 553 (1)| 00:00:07 |KEY(SQ)|KEY(SQ)| | 7 | TABLE ACCESS BY LOCAL INDEX ROWID| SALES | 507 | 10647 | 553 (1)| 00:00:07 |KEY(SQ)|KEY(SQ)| | 8 | BITMAP CONVERSION TO ROWIDS | | | | | | | | | 9 | BITMAP AND | | | | | | | | | 10 | BITMAP MERGE | | | | | | | | | 11 | BITMAP KEY ITERATION | | | | | | | | | 12 | BUFFER SORT | | | | | | | | |* 13 | TABLE ACCESS FULL | CHANNELS | 2 | 42 | 3 (0)| 00:00:01 | | | |* 14 | BITMAP INDEX RANGE SCAN | SALES_CHANNEL_BIX | | | | |KEY(SQ)|KEY(SQ)| | 15 | BITMAP MERGE | | | | | | | | | 16 | BITMAP KEY ITERATION | | | | | | | | | 17 | BUFFER SORT | | | | | | | | |* 18 | TABLE ACCESS FULL | TIMES | 365 | 5840 | 18 (0)| 00:00:01 | | | |* 19 | BITMAP INDEX RANGE SCAN | SALES_TIME_BIX | | | | |KEY(SQ)|KEY(SQ)| | 20 | BITMAP MERGE | | | | | | | | | 21 | BITMAP KEY ITERATION | | | | | | | | | 22 | BUFFER SORT | | | | | | | | |* 23 | TABLE ACCESS FULL | CUSTOMERS | 383 | 9958 | 406 (1)| 00:00:05 | | | |* 24 | BITMAP INDEX RANGE SCAN | SALES_CUST_BIX | | | | |KEY(SQ)|KEY(SQ)| |* 25 | TABLE ACCESS FULL | TIMES | 365 | 5840 | 18 (0)| 00:00:01 | | | |* 26 | TABLE ACCESS FULL | CHANNELS | 2 | 42 | 3 (0)| 00:00:01 | | | --------------------------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 3 4 5 13 14 18

-

19 23 24 25

-

26 -

access("S"."CHANNEL_ID"="CH"."CHANNEL_ID") access("S"."TIME_ID"="T"."TIME_ID") access("S"."CUST_ID"="C"."CUST_ID") filter("C"."CUST_STATE_PROVINCE"='CA') filter("CH"."CHANNEL_DESC"='Catalog' OR "CH"."CHANNEL_DESC"='Internet') access("S"."CHANNEL_ID"="CH"."CHANNEL_ID") filter("T"."CALENDAR_QUARTER_DESC"='1999-01' OR "T"."CALENDAR_QUARTER_DESC"='1999-02' OR "T"."CALENDAR_QUARTER_DESC"='2000-03' OR "T"."CALENDAR_QUARTER_DESC"='2000-04') access("S"."TIME_ID"="T"."TIME_ID") filter("C"."CUST_STATE_PROVINCE"='CA') access("S"."CUST_ID"="C"."CUST_ID") filter("T"."CALENDAR_QUARTER_DESC"='1999-01' OR "T"."CALENDAR_QUARTER_DESC"='1999-02' OR "T"."CALENDAR_QUARTER_DESC"='2000-03' OR "T"."CALENDAR_QUARTER_DESC"='2000-04') filter("CH"."CHANNEL_DESC"='Catalog' OR "CH"."CHANNEL_DESC"='Internet')

Note ----- star transformation used for this statement




Practice 6-1: Star Schema Tuning (continued)

Practice 6-1: Star Schema Tuning (continued) 2130 0 1896 442 4 147 0 41


SQL> --------------------------------------------------------------

alter system flush shared_pool; alter system flush buffer_cache; set set set set


ALTER SESSION SET star_transformation_enabled=TEMP_DISABLE;


4) How would you enhance the previous optimization without changing the SH schema? a) Let the optimizer decide if it is better to use a temporary table. You can try to set the STAR_TRANSFORMATION_ENABLED parameter to TRUE. SQL> @third_run SQL> set echo on SQL> SQL> alter system flush shared_pool; System altered. Elapsed: 00:00:00.10 SQL> alter system flush buffer_cache;



set echo on

Practice 6-1: Star Schema Tuning (continued) System altered. Elapsed: 00:00:00.21 SQL> SQL> set pagesize 200 SQL> set linesize 250 SQL> set timing on SQL> set autotrace on SQL> SQL> ALTER SESSION SET star_transformation_enabled=TRUE;

Elapsed: 00:00:00.00 SQL> SQL> SELECT ch.channel_class, c.cust_city, t.calendar_quarter_desc, 2 SUM(s.amount_sold) sales_amount 3 FROM sales s, times t, customers c, channels ch 4 WHERE s.time_id = t.time_id 5 AND s.cust_id = c.cust_id 6 AND s.channel_id = ch.channel_id 7 AND c.cust_state_province = 'CA' 8 AND ch.channel_desc in ('Internet','Catalog') 9 AND t.calendar_quarter_desc IN ('1999-01','1999-02','200003','2000-04') 10 GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc; CHANNEL_CLASS SALES_AMOUNT ----------------------Indirect 13227.99 Indirect 1319 … Indirect 3058.27 Indirect 3263.93

CUST_CITY

CALENDA

------------------------------ ------- -------San Francisco

2000-04

Montara

2000-04

San Francisco

1999-01

Pala

1999-01

41 rows selected. Elapsed: 00:00:00.30 Execution Plan ---------------------------------------------------------Plan hash value: 163104418 ----------------------------------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | Pstart| Pstop | ----------------------------------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 3 | 219 | 985 (1)| 00:00:12 | | | | 1 | TEMP TABLE TRANSFORMATION | | | | | | | | | 2 | LOAD AS SELECT | SYS_TEMP_0FD9D660F_8947E | | | | | | | |* 3 | TABLE ACCESS FULL | CUSTOMERS | 383 | 9958 | 406 (1)| 00:00:05 | | |



Session altered.

| 4 | HASH GROUP BY | | 3 | 219 | 579 (2)| 00:00:07 | | | |* 5 | HASH JOIN | | 3 | 219 | 578 (1)| 00:00:07 | | | |* 6 | HASH JOIN | | 7 | 364 | 574 (1)| 00:00:07 | | | |* 7 | HASH JOIN | | 28 | 1008 | 556 (1)| 00:00:07 | | | | 8 | TABLE ACCESS FULL | SYS_TEMP_0FD9D660F_8947E | 383 | 5745 | 2 (0)| 00:00:01 | | | | 9 | PARTITION RANGE SUBQUERY | | 507 | 10647 | 553 (1)| 00:00:07 |KEY(SQ)|KEY(SQ)| | 10 | TABLE ACCESS BY LOCAL INDEX ROWID| SALES | 507 | 10647 | 553 (1)| 00:00:07 |KEY(SQ)|KEY(SQ)| | 11 | BITMAP CONVERSION TO ROWIDS | | | | | | | | | 12 | BITMAP AND | | | | | | | | | 13 | BITMAP MERGE | | | | | | | | | 14 | BITMAP KEY ITERATION | | | | | | | | | 15 | BUFFER SORT | | | | | | | | |* 16 | TABLE ACCESS FULL | CHANNELS | 2 | 42 | 3 (0)| 00:00:01 | | | |* 17 | BITMAP INDEX RANGE SCAN | SALES_CHANNEL_BIX | | | | |KEY(SQ)|KEY(SQ)| | 18 | BITMAP MERGE | | | | | | | | | 19 | BITMAP KEY ITERATION | | | | | | | | | 20 | BUFFER SORT | | | | | | | | |* 21 | TABLE ACCESS FULL | TIMES | 365 | 5840 | 18 (0)| 00:00:01 | | | |* 22 | BITMAP INDEX RANGE SCAN | SALES_TIME_BIX | | | | |KEY(SQ)|KEY(SQ)| | 23 | BITMAP MERGE | | | | | | | | | 24 | BITMAP KEY ITERATION | | | | | | | | | 25 | BUFFER SORT | | | | | | | | | 26 | TABLE ACCESS FULL | SYS_TEMP_0FD9D660F_8947E | 1 | 13 | 2 (0)| 00:00:01 | | | |* 27 | BITMAP INDEX RANGE SCAN | SALES_CUST_BIX | | | | |KEY(SQ)|KEY(SQ)| |* 28 | TABLE ACCESS FULL | TIMES | 365 | 5840 | 18 (0)| 00:00:01 | | | |* 29 | TABLE ACCESS FULL | CHANNELS | 2 | 42 | 3 (0)| 00:00:01 | | | ----------------------------------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------3 5 6 7 16 17 21

-

22 27 28 29 -

filter("C"."CUST_STATE_PROVINCE"='CA') access("S"."CHANNEL_ID"="CH"."CHANNEL_ID") access("S"."TIME_ID"="T"."TIME_ID") access("S"."CUST_ID"="C0") filter("CH"."CHANNEL_DESC"='Catalog' OR "CH"."CHANNEL_DESC"='Internet') access("S"."CHANNEL_ID"="CH"."CHANNEL_ID") filter("T"."CALENDAR_QUARTER_DESC"='1999-01' OR "T"."CALENDAR_QUARTER_DESC"='1999-02' OR "T"."CALENDAR_QUARTER_DESC"='2000-03' OR "T"."CALENDAR_QUARTER_DESC"='2000-04') access("S"."TIME_ID"="T"."TIME_ID") access("S"."CUST_ID"="C0") filter("T"."CALENDAR_QUARTER_DESC"='1999-01' OR "T"."CALENDAR_QUARTER_DESC"='1999-02' OR "T"."CALENDAR_QUARTER_DESC"='2000-03' OR "T"."CALENDAR_QUARTER_DESC"='2000-04') filter("CH"."CHANNEL_DESC"='Catalog' OR "CH"."CHANNEL_DESC"='Internet')


Statistics ---------------------------------------------------------17911 recursive calls 19 db block gets 35577 consistent gets 2157 physical reads 1616 redo size 1896 bytes sent via SQL*Net to client 442 bytes received via SQL*Net from client 4 SQL*Net roundtrips to/from client




Practice 6-1: Star Schema Tuning (continued) 155 0 41

sorts (memory) sorts (disk) rows processed

SQL> SQL>

-------------------------------------------------------------set echo on

set set set set


ALTER SESSION SET star_transformation_enabled=TRUE; SELECT ch.channel_class, c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold) sales_amount FROM sales s, times t, customers c, channels ch WHERE s.time_id = t.time_id AND s.cust_id = c.cust_id AND s.channel_id = ch.channel_id AND c.cust_state_province = 'CA' AND ch.channel_desc in ('Internet','Catalog') AND t.calendar_quarter_desc IN ('1999-01','1999-02','200003','2000-04') GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc;

5) How do you eliminate one table access on the CUSTOMERS table from the previous execution plan for the same SELECT statement seen in step 3? a) Create a bitmap join index between the SALES and CUSTOMERS tables. 6) Try to apply your finding. What happens and why? a) Because the CUSTOMERS_PK primary key constraint is not enforced, it is not possible to create a bitmap join index between the SALES and CUSTOMERS tables. SQL> @create_bji.sql SQL> SQL> CREATE BITMAP INDEX sales_c_state_bjix ON sales(customers.cust_state_province) FROM sales, customers WHERE sales.cust_id=customers.cust_id 2 LOCAL NOLOGGING COMPUTE STATISTICS; CREATE BITMAP INDEX sales_c_state_bjix ON sales(customers.cust_state_province) FROM sales, customers WHERE sales.cust_id=customers.cust_id




Practice 6-1: Star Schema Tuning (continued) * ERROR at line 1: ORA-25954: missing primary key or unique constraint on dimension

SQL> --------------------------------------------------------------

CREATE BITMAP INDEX sales_c_state_bjix ON sales(customers.cust_state_province) FROM sales, customers WHERE sales.cust_id=customers.cust_id LOCAL NOLOGGING COMPUTE STATISTICS;

7) Fix the issue you found and apply your solution from step 5 again. a) You need to ENABLE VALIDATE the CUSTOMERS_PK constraint before you can create the bitmap join index. SQL> @recreate_bji SQL> SQL> alter table customers enable constraint customers_pk; Table altered. SQL> SQL> CREATE BITMAP INDEX sales_c_state_bjix ON sales(customers.cust_state_province) FROM sales, customers WHERE sales.cust_id=customers.cust_id 2 LOCAL NOLOGGING COMPUTE STATISTICS; Index created. SQL> SQL> -------------------------------------------------------------set echo on alter table customers enable constraint customers_pk; CREATE BITMAP INDEX sales_c_state_bjix ON sales(customers.cust_state_province) FROM sales, customers WHERE sales.cust_id=customers.cust_id LOCAL NOLOGGING COMPUTE STATISTICS;

8) Verify that you solved the problem from step 5. SQL> @fourth_run



set echo on

Practice 6-1: Star Schema Tuning (continued) SQL> set echo on SQL> SQL> ALTER SESSION SET star_transformation_enabled=TRUE; Session altered. SQL> SQL> alter system flush shared_pool; System altered. SQL> alter system flush buffer_cache;

SQL> SQL> set pagesize 200 SQL> set linesize 250 SQL> set timing on SQL> set autotrace on SQL> SQL> SELECT ch.channel_class, c.cust_city, t.calendar_quarter_desc, 2 SUM(s.amount_sold) sales_amount 3 FROM sales s, times t, customers c, channels ch 4 WHERE s.time_id = t.time_id 5 AND s.cust_id = c.cust_id 6 AND s.channel_id = ch.channel_id 7 AND c.cust_state_province = 'CA' 8 AND ch.channel_desc in ('Internet','Catalog') 9 AND t.calendar_quarter_desc IN ('1999-01','1999-02','200003','2000-04') 10 GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc; CHANNEL_CLASS SALES_AMOUNT ----------------------Indirect 987.3 Indirect 241.2 Indirect … Indirect 1618.01 Indirect 412.83

CUST_CITY

CALENDA

------------------------------ ------- -------Quartzhill

1999-01

Arbuckle

1999-02

Pala

2000-03

Montara

1999-02

Quartzhill

1999-02

41 rows selected. Elapsed: 00:00:00.23 Execution Plan ---------------------------------------------------------Plan hash value: 632695221 ----------------------------------------------------------------------------------------------------------------------------



System altered.

| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | Pstart| Pstop | ---------------------------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 498 | 41832 | 557 (2)| 00:00:07 | | | | 1 | HASH GROUP BY | | 498 | 41832 | 557 (2)| 00:00:07 | | | |* 2 | HASH JOIN | | 498 | 41832 | 556 (2)| 00:00:07 | | | |* 3 | TABLE ACCESS FULL | CHANNELS | 2 | 42 | 3 (0)| 00:00:01 | | | |* 4 | HASH JOIN | | 996 | 62748 | 552 (1)| 00:00:07 | | | |* 5 | TABLE ACCESS FULL | TIMES | 365 | 5840 | 18 (0)| 00:00:01 | | | |* 6 | HASH JOIN | | 3984 | 182K| 533 (1)| 00:00:07 | | | |* 7 | TABLE ACCESS FULL | CUSTOMERS | 383 | 9958 | 406 (1)| 00:00:05 | | | | 8 | PARTITION RANGE SUBQUERY | | 73467 | 1506K| 126 (1)| 00:00:02 |KEY(SQ)|KEY(SQ)| | 9 | TABLE ACCESS BY LOCAL INDEX ROWID| SALES | 73467 | 1506K| 126 (1)| 00:00:02 |KEY(SQ)|KEY(SQ)| | 10 | BITMAP CONVERSION TO ROWIDS | | | | | | | | | 11 | BITMAP AND | | | | | | | | | 12 | BITMAP MERGE | | | | | | | | | 13 | BITMAP KEY ITERATION | | | | | | | | | 14 | BUFFER SORT | | | | | | | | |* 15 | TABLE ACCESS FULL | CHANNELS | 2 | 42 | 3 (0)| 00:00:01 | | | |* 16 | BITMAP INDEX RANGE SCAN | SALES_CHANNEL_BIX | | | | |KEY(SQ)|KEY(SQ)| | 17 | BITMAP MERGE | | | | | | | | | 18 | BITMAP KEY ITERATION | | | | | | | | | 19 | BUFFER SORT | | | | | | | | |* 20 | TABLE ACCESS FULL | TIMES | 365 | 5840 | 18 (0)| 00:00:01 | | | |* 21 | BITMAP INDEX RANGE SCAN | SALES_TIME_BIX | | | | |KEY(SQ)|KEY(SQ)| |* 22 | BITMAP INDEX SINGLE VALUE | SALES_C_STATE_BJIX | | | | |KEY(SQ)|KEY(SQ)| ---------------------------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 3 4 5

-

6 7 15 16 20

-

21 22 -

access("S"."CHANNEL_ID"="CH"."CHANNEL_ID") filter("CH"."CHANNEL_DESC"='Catalog' OR "CH"."CHANNEL_DESC"='Internet') access("S"."TIME_ID"="T"."TIME_ID") filter("T"."CALENDAR_QUARTER_DESC"='1999-01' OR "T"."CALENDAR_QUARTER_DESC"='1999-02' OR "T"."CALENDAR_QUARTER_DESC"='2000-03' OR "T"."CALENDAR_QUARTER_DESC"='2000-04') access("S"."CUST_ID"="C"."CUST_ID") filter("C"."CUST_STATE_PROVINCE"='CA') filter("CH"."CHANNEL_DESC"='Catalog' OR "CH"."CHANNEL_DESC"='Internet') access("S"."CHANNEL_ID"="CH"."CHANNEL_ID") filter("T"."CALENDAR_QUARTER_DESC"='1999-01' OR "T"."CALENDAR_QUARTER_DESC"='1999-02' OR "T"."CALENDAR_QUARTER_DESC"='2000-03' OR "T"."CALENDAR_QUARTER_DESC"='2000-04') access("S"."TIME_ID"="T"."TIME_ID") access("S"."SYS_NC00008$"='CA')


Statistics ---------------------------------------------------------18151 recursive calls 0 db block gets 8759 consistent gets 2002 physical reads 0 redo size 1888 bytes sent via SQL*Net to client 442 bytes received via SQL*Net from client 4 SQL*Net roundtrips to/from client 154 sorts (memory) 0 sorts (disk)




Practice 6-1: Star Schema Tuning (continued) 41

rows processed

SQL> -------------------------------------------------------------set echo on ALTER SESSION SET star_transformation_enabled=TRUE;

set set set set



9) Determine how the system could dynamically determine which SALES partitions to access for the previous query. a) View the OTHER column of PLAN_TABLE for the PARTITION RANGE operation. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL>

@dynamic_partition_pruning set autotrace off set timing off set long 4000 alter session set star_transformation_enabled=true;

Session altered. SQL> SQL> 2 3 4 5 6 7 8

explain plan for SELECT ch.channel_class, c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold) sales_amount FROM sales s, times t, customers c, channels ch WHERE s.time_id = t.time_id AND s.cust_id = c.cust_id AND s.channel_id = ch.channel_id AND c.cust_state_province = 'CA'




Practice 6-1: Star Schema Tuning (continued) 9 AND ch.channel_desc in ('Internet','Catalog') 10 AND t.calendar_quarter_desc IN ('1999-01','1999-02','200003','2000-04') 11 GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc; Explained.

OTHER ------------------------------------------------------------------------------SELECT distinct TBL$OR$IDX$PART$NUM("SALES", 0, d#, p#, PAP_ALIAS_0."PAP_COL_ALI AS_0") FROM (SELECT /*+ SEMIJOIN_DRIVER */ "T"."TIME_ID" "PAP_COL_ALIAS_0" FROM "TIMES" "T" WHERE "T"."CALENDAR_QUARTER_DESC"='1999-01' OR "T"."CALENDAR_QUARTER _DESC"='1999-02' OR "T"."CALENDAR_QUARTER_DESC"='2000-03' OR "T"."CALENDAR_QUART ER_DESC"='2000-04') PAP_ALIAS_0 ORDER BY 1

SQL>

-------------------------------------------------------------set echo on set autotrace off set timing off set long 4000 alter session set star_transformation_enabled=true; explain plan for SELECT ch.channel_class, c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold) sales_amount FROM sales s, times t, customers c, channels ch WHERE s.time_id = t.time_id AND s.cust_id = c.cust_id AND s.channel_id = ch.channel_id AND c.cust_state_province = 'CA' AND ch.channel_desc in ('Internet','Catalog') AND t.calendar_quarter_desc IN ('1999-01','1999-02','200003','2000-04') GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc; SELECT other FROM plan_table WHERE operation='PARTITION RANGE';



SQL> SQL> SELECT other 2 FROM plan_table 3 WHERE operation='PARTITION RANGE';

Practice 6-1: Star Schema Tuning (continued) 10) Clean up your environment by removing the index you created and returning the constraint to its original state. SQL> SQL> SQL> SQL> SQL> SQL> SQL>

@cleanup_star_schema_lab set echo on set timing off set autotrace off drop index sales_c_state_bjix;

SQL> SQL> alter table customers enable novalidate constraint customers_pk; Table altered. SQL> SQL> connect / as sysdba Connected. SQL> SQL> revoke dba from sh; Revoke succeeded. SQL> SQL> exit Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Star_Schema_Tuning]$ -------------------------------------------------------------set echo on set timing off set autotrace off drop index sales_c_state_bjix; alter table customers enable novalidate constraint customers_pk; connect / as sysdba revoke dba from sh; exit;



Index dropped.




Practice 7-1: Using System Statistics In this practice, you manipulate system statistics and show that they are important for the optimizer to select the correct execution plans. 1. Connected as the oracle user in a terminal session, execute the sysstats_setup.sh script located in your $HOME/solutions/System_Stats directory. This script creates a user called JFV and some tables used throughout this lab. The script also makes sure that object statistics are correctly gathered.

SQL*Plus: Release 11.1.0.6.0 - Production on Mon Mar 31 19:11:42 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> connect / as sysdba; Connected. SQL> SQL> drop user jfv cascade; User dropped. SQL> SQL> create user jfv identified by jfv default tablespace users temporary tablespace temp; User created. SQL> SQL> grant connect, resource, dba to jfv; Grant succeeded. SQL> SQL> SQL> connect jfv/jfv Connected. SQL> SQL> drop table t purge; drop table t purge * ERROR at line 1: ORA-00942: table or view does not exist



[oracle@edrsr33p1-orcl ~]$ cd $HOME/solutions/System_Stats [oracle@edrsr33p1-orcl System_Stats]$ [oracle@edrsr33p1-orcl System_Stats]$ ./sysstats_setup.sh

Practice 7-1: Using System Statistics (continued) SQL> SQL> drop table z purge; drop table z purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> SQL> create table t(c number);

SQL> SQL> insert into t values (1); 1 row created. SQL> SQL> commit; Commit complete. SQL> SQL> insert into t select * from t; 1 row created. SQL> SQL> / 2 rows created. SQL> / 4 rows created. SQL> / 8 rows created. SQL> / 16 rows created. SQL> / 32 rows created. SQL> / 64 rows created. SQL> /



Table created.

Practice 7-1: Using System Statistics (continued) 128 rows created. SQL> / 256 rows created. SQL> / 512 rows created. SQL> /

SQL> SQL> commit; Commit complete. SQL> SQL> insert into t select * from t; 2048 rows created. SQL> SQL> / 4096 rows created. SQL> / 8192 rows created. SQL> / 16384 rows created. SQL> / 32768 rows created. SQL> / 65536 rows created. SQL> / 131072 rows created. SQL> / 262144 rows created. SQL> SQL> commit; Commit complete.



1024 rows created.

Practice 7-1: Using System Statistics (continued) SQL> SQL> create table z(d number); Table created.

PL/SQL procedure successfully completed. SQL> SQL> create unique index iz on z(d); Index created. SQL> SQL> execute dbms_stats.gather_table_stats('JFV','T',cascade=>true); PL/SQL procedure successfully completed. SQL> SQL> execute dbms_stats.gather_table_stats('JFV','Z',cascade=>true); PL/SQL procedure successfully completed. SQL> SQL> SQL> SQL> connect / as sysdba; Connected. SQL> SQL> alter system flush shared_pool; System altered. SQL> SQL> alter system flush buffer_cache; System altered. SQL> SQL> execute dbms_stats.delete_system_stats; PL/SQL procedure successfully completed. SQL> SQL> execute DBMS_STATS.SET_SYSTEM_STATS (pname => 'cpuspeednw', pvalue => 0); PL/SQL procedure successfully completed.



SQL> SQL> begin 2 for i in 1..100 loop 3 insert into z values (i); 4 end loop; 5 commit; 6 end; 7 /

Practice 7-1: Using System Statistics (continued) SQL> SQL> select sname,pname,pval1 from aux_stats$; SNAME PVAL1 --------------------------------SYSSTATS_INFO SYSSTATS_INFO SYSSTATS_INFO SYSSTATS_INFO 1 SYSSTATS_MAIN 0 SYSSTATS_MAIN 10 SYSSTATS_MAIN 4096 SYSSTATS_MAIN SYSSTATS_MAIN SYSSTATS_MAIN SYSSTATS_MAIN

PNAME

SNAME PVAL1 --------------------------------SYSSTATS_MAIN SYSSTATS_MAIN

PNAME

------------------------------ -----STATUS DSTART DSTOP FLAGS

IOSEEKTIM IOTFRSPEED SREADTIM MREADTIM CPUSPEED MBRC

------------------------------ -----MAXTHR SLAVETHR

13 rows selected. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl System_Stats]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/System_Stats export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @sysstats_setup.sql



CPUSPEEDNW

Practice 7-1: Using System Statistics (continued) [oracle@edrsr33p1-orcl System_Stats]$ -------------------------------------------------------------set echo on connect / as sysdba; drop user jfv cascade; create user jfv identified by jfv default tablespace users temporary tablespace temp;

connect jfv/jfv drop table t purge; drop table z purge; create table t(c number); insert into t values (1); commit; insert into t select * from t; / / / / / / / / / / commit; insert into t select * from t; / / / / / / / commit; create table z(d number);



grant connect, resource, dba to jfv;

Practice 7-1: Using System Statistics (continued) begin for i in 1..100 loop insert into z values (i); end loop; commit; end; / create unique index iz on z(d); execute dbms_stats.gather_table_stats('JFV','T',cascade=>true);

connect / as sysdba; alter system flush shared_pool; alter system flush buffer_cache; execute dbms_stats.delete_system_stats; execute DBMS_STATS.SET_SYSTEM_STATS (pname => 'cpuspeednw', pvalue => 0); select sname,pname,pval1 from aux_stats$; exit;

2. From your terminal session, connect as the JFV user in the SQL*Plus session. After this, execute the following statement and determine how long it takes to execute: select /* Without system stats */ count(*) from t,z where t.c=z.d; [oracle@edrsr33p1-orcl System_Stats]$ sqlplus jfv/jfv SQL*Plus: Release 11.1.0.6.0 - Production on Mon Mar 31 19:11:57 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> @select_without_sysstats SQL> SQL> set timing on SQL>



execute dbms_stats.gather_table_stats('JFV','Z',cascade=>true);

Practice 7-1: Using System Statistics (continued) SQL> select /* Without system stats */ count(*) 2 from t,z 3 where t.c=z.d; COUNT(*) ---------524288

-------------------------------------------------------------set echo on set timing on select /* Without system stats */ count(*) from t,z where t.c=z.d; set timing off

3. Determine the execution plan used to execute the previous statement. In addition, determine the optimizer’s cost, CPU cost, and I/O cost for the previous execution. What do you observe? a) The optimizer does not use CPU costing. This is because system statistics were deleted during the first step of this lab. The plan chosen by the optimizer might not be the best one. SQL> @show_latest_exec_plan SQL> set echo on SQL> SQL> select * from table(dbms_xplan.display_cursor); PLAN_TABLE_OUTPUT ------------------------------------------------------------------------------SQL_ID 6avdu58tamzju, child number 0 ------------------------------------select /* Without system stats */ count(*) from t,z where t.c=z.d Plan hash value: 3698032250 -----------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost | -----------------------------------------------------------| 0 | SELECT STATEMENT | | | | 134 | | 1 | SORT AGGREGATE | | 1 | 6 | | PLAN_TABLE_OUTPUT -------------------------------------------------------------------------------



Elapsed: 00:00:00.24 SQL> SQL> set timing off SQL> SQL>

Practice 7-1: Using System Statistics (continued) | 2 | NESTED LOOPS | | 524K| 3072K| 134 | | 3 | TABLE ACCESS FULL| T | 524K| 1536K| 134 | |* 4 | INDEX UNIQUE SCAN| IZ | 1 | 3 | | -----------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------4 - access("T"."C"="Z"."D")

PLAN_TABLE_OUTPUT ----------------------------------------------------------------------------------- cpu costing is off (consider enabling it)

25 rows selected. SQL> SQL> col operations format a20 SQL> col object_name format a11 SQL> col options format a15 SQL> col cost_cpu_io format a30 SQL> SQL> SQL> select operation operations, object_name, options, 2 cost||' -- '||cpu_cost||' -- '||io_cost cost_cpu_io 3 from (select * from v$sql_plan where address in (select address 4 from v$sql 5 where sql_text like '%system stats%' and 6 sql_text not like '%connect%')); OPERATIONS -----------------------------SELECT STATEMENT SORT NESTED LOOPS TABLE ACCESS INDEX

OBJECT_NAME OPTIONS COST_CPU_IO ----------- --------------- -------------------

AGGREGATE T IZ

FULL UNIQUE SCAN

134 -- --- -134 -- -- 134 134 -- -- 134 -- --

SQL> -------------------------------------------------------------set echo on select * from table(dbms_xplan.display_cursor); col operations format a20 col object_name format a11 col options format a15



Note

Practice 7-1: Using System Statistics (continued) col cost_cpu_io format a30 select operation operations, object_name, options, cost||' -- '||cpu_cost||' -- '||io_cost cost_cpu_io from (select * from v$sql_plan where address in (select address from v$sql where sql_text like '%system stats%' and sql_text not like '%connect%'));

b) Gather system statistics again. Because you do not have yet a real workload, you can gather system statistics in NOWORKLOAD mode. SQL> connect / as sysdba; Connected. SQL> @gather_system_stats SQL> set echo on SQL> SQL> execute DBMS_STATS.GATHER_SYSTEM_STATS(gathering_mode => 'NOWORKLOAD'); PL/SQL procedure successfully completed. SQL> SQL> select sname,pname,pval1 from aux_stats$; SNAME PVAL1 --------------------------------SYSSTATS_INFO SYSSTATS_INFO SYSSTATS_INFO SYSSTATS_INFO 1 SYSSTATS_MAIN 1893.021 SYSSTATS_MAIN 8.043 SYSSTATS_MAIN 4096 SYSSTATS_MAIN SYSSTATS_MAIN SYSSTATS_MAIN SYSSTATS_MAIN

PNAME ------------------------------ -----STATUS DSTART DSTOP FLAGS CPUSPEEDNW IOSEEKTIM IOTFRSPEED SREADTIM MREADTIM CPUSPEED MBRC

SNAME PNAME PVAL1 ------------------------------ ------------------------------ --------SYSSTATS_MAIN MAXTHR



4. How can you ensure that the optimizer finds a better plan during future executions of the same statement? Implement your solution.

Practice 7-1: Using System Statistics (continued) SYSSTATS_MAIN

SLAVETHR

13 rows selected. SQL> -------------------------------------------------------------set echo on execute DBMS_STATS.GATHER_SYSTEM_STATS(gathering_mode => 'NOWORKLOAD');

5. Before verifying your solution, you should flush the System Global Area (SGA) pools, such as the shared pool and the buffer cache. This is done to prevent interferences from the previous steps. SQL> @flush_sga SQL> SQL> set echo on SQL> SQL> alter system flush shared_pool; System altered. SQL> SQL> alter system flush buffer_cache; System altered. SQL> SQL> -------------------------------------------------------------set echo on alter system flush shared_pool; alter system flush buffer_cache;

6. Connected as the JFV user again, check your solution against the following query: select /* With system stats */ count(*) from t,z where t.c=z.d;

What do you observe? c) The optimizer can make a better decision because it was able to use meaningful system statistics. You can see that the execution time is now half the value it was previously, and the execution plan now includes CPU costing information.



select sname,pname,pval1 from aux_stats$;

Practice 7-1: Using System Statistics (continued) SQL> connect jfv/jfv Connected. SQL> @select_with_sysstats SQL> set timing on SQL> SQL> select /* With system stats */ count(*) 2 from t,z 3 where t.c=z.d;

Elapsed: 00:00:00.11 SQL> SQL> set timing off SQL> SQL> @show_latest_exec_plan SQL> set echo on SQL> SQL> select * from table(dbms_xplan.display_cursor); PLAN_TABLE_OUTPUT ------------------------------------------------------------------------------SQL_ID 2x55txn3742by, child number 0 ------------------------------------select /* With system stats */ count(*) from t,z where t.c=z.d Plan hash value: 2407521827 --------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------| 0 | SELECT STATEMENT | | | | 272 (100)| | | 1 | SORT AGGREGATE | | 1 | 6 | | | PLAN_TABLE_OUTPUT ------------------------------------------------------------------------------|* 2 | HASH JOIN | | 524K| 3072K| 272 (3)| 00:00:03 | | 3 | INDEX FULL SCAN | IZ | 100 | 300 | 1 (0)| 00:00:01 | | 4 | TABLE ACCESS FULL| T | 524K| 1536K| 267 (2)| 00:00:03 | --------------------------------------------------------------------------Predicate Information (identified by operation id): ---------------------------------------------------



COUNT(*) ---------524288

Practice 7-1: Using System Statistics (continued) 2 - access("T"."C"="Z"."D")

SQL> SQL> col operations format a20 SQL> col object_name format a11 SQL> col options format a15 SQL> col cost_cpu_io format a30 SQL> SQL> SQL> select operation operations, object_name, options, 2 cost||' -- '||cpu_cost||' -- '||io_cost cost_cpu_io 3 from (select * from v$sql_plan where address in (select address 4 from v$sql 5 where sql_text like '%system stats%' and 6 sql_text not like '%connect%')); OPERATIONS -----------------------------SELECT STATEMENT SORT HASH JOIN 264 INDEX TABLE ACCESS 263

OBJECT_NAME OPTIONS COST_CPU_IO ----------- --------------- -------------------

IZ T

AGGREGATE

272 -- --- -272 -- 146844065 --

FULL SCAN FULL

1 -- 27121 -- 1 267 -- 84867339 --

SQL> -------------------------------------------------------------set timing on select /* With system stats */ count(*) from t,z where t.c=z.d; set timing off -------------------------------------------------------------set echo on select * from table(dbms_xplan.display_cursor); col col col col

operations object_name options cost_cpu_io

format format format format

a20 a11 a15 a30

select operation operations, object_name, options,



21 rows selected.

Practice 7-1: Using System Statistics (continued) cost||' -- '||cpu_cost||' -- '||io_cost cost_cpu_io from (select * from v$sql_plan where address in (select address from v$sql where sql_text like '%system stats%' and sql_text not like '%connect%'));

SQL> exit Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl System_Stats]$ ./sysstats_cleanup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Mon Mar 31 19:13:54 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> drop user jfv cascade; User dropped. SQL> SQL> alter system flush shared_pool; System altered. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl System_Stats]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/System_Stats export ORACLE_SID=orcl



7. Exit from your SQL*Plus session and clean up your environment for this lab by executing the systats_cleanup.sh script.

Practice 7-1: Using System Statistics (continued) export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @sysstats_cleanup.sql -------------------------------------------------------------set echo on

alter system flush shared_pool; exit;



drop user jfv cascade;

Practice 7-2: Automatic Statistics Gathering In this practice, you manipulate object statistics to see their incidences on the execution plans of your SQL statements. Note: All scripts needed for this lab can be found in your $HOME/solutions/Automatic_Gather_Stats directory. 1) From a terminal window connected as the oracle user, set up your environment for this lab by executing the ags_setup.sh script. This script creates a user called AGS that you use throughout this lab. The script also creates a table called EMP and an index. [oracle@edrsr33p1-orcl Automatic_Gather_Stats]$ ./ags_setup.sh



Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> drop user ags cascade; drop user ags cascade * ERROR at line 1: ORA-01918: user 'AGS' does not exist

SQL> SQL> create user ags identified by ags; User created. SQL> SQL> grant dba to ags; Grant succeeded. SQL> SQL> alter system flush shared_pool; System altered. SQL> SQL> SQL> SQL> SQL> SQL>

--- Turn off AUTOTASK -alter system set "_enable_automatic_maintenance"=0;

System altered.



SQL*Plus: Release 11.1.0.6.0 - Production on Mon Apr 7 15:55:28 2008

Practice 7-2: Automatic Statistics Gathering (continued)

SQL> SQL> create table emp 2 ( 3 empno number, 4 ename varchar2(20), 5 phone varchar2(20), 6 deptno number 7 ); Table created. SQL> SQL> SQL> insert into emp 2 with tdata as 3 (select rownum empno 4 from all_objects 5 where rownum <= 1000) 6 select rownum, 7 dbms_random.string ('u', 20), 8 dbms_random.string ('u', 20), 9 case 10 when rownum/100000 <= 0.001 then mod(rownum, 10) 11 else 10 12 end 13 from tdata a, tdata b 14 where rownum <= 100000; 100000 rows created. SQL> SQL> commit; Commit complete. SQL> SQL> create index emp_i1 on emp(deptno); Index created. SQL> SQL> exec dbms_stats.delete_schema_stats('AGS'); PL/SQL procedure successfully completed.



SQL> SQL> connect ags/ags Connected. SQL> SQL> drop table emp purge; drop table emp purge * ERROR at line 1: ORA-00942: table or view does not exist

Practice 7-2: Automatic Statistics Gathering (continued) SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Automatic_Gather_Stats]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Automatic_Gather_Stats

export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin sqlplus / as sysdba @ags_setup.sql -------------------------------------------------------------set echo on drop user ags cascade; create user ags identified by ags; grant dba to ags; alter system flush shared_pool; --- Turn off AUTOTASK -alter system set "_enable_automatic_maintenance"=0; connect ags/ags drop table emp purge; create table emp ( empno number, ename varchar2(20), phone varchar2(20), deptno number );

insert into emp with tdata as



export ORACLE_SID=orcl

Practice 7-2: Automatic Statistics Gathering (continued) (select rownum empno from all_objects where rownum <= 1000) select rownum, dbms_random.string ('u', 20), dbms_random.string ('u', 20), case when rownum/100000 <= 0.001 then mod(rownum, 10) else 10 end from tdata a, tdata b where rownum <= 100000;

create index emp_i1 on emp(deptno); exec dbms_stats.delete_schema_stats('AGS'); exit;

2) Connect as the AGS user under a SQL*Plus session. [oracle@edrsr33p1-orcl Automatic_Gather_Stats]$ sqlplus ags/ags SQL*Plus: Release 11.1.0.6.0 - Production on Mon Apr 7 15:55:47 2008 Copyright (c) 1982, 2007, Oracle.



3) Determine the distribution of the deptno values found in the EMP table. What do you observe? a) You can see that there are 11 different department values, each repeating 0.01% of the time except value 10 that repeats 99.9% of the time. SQL> @show_deptno_distribution SQL> SQL> select deptno, count(*) cnt_per_deptno, (count(*)*100)/nr deptno_percent 2 from emp, (select max(empno) nr 3 from emp) 4 group by deptno, nr 5 order by deptno; DEPTNO CNT_PER_DEPTNO DEPTNO_PERCENT ---------- -------------- -------------0 10 .01



commit;

Practice 7-2: Automatic Statistics Gathering (continued) 1 2 3 4 5 6 7 8 9 10

10 10 10 10 10 10 10 10 10 99900

.01 .01 .01 .01 .01 .01 .01 .01 .01 99.9

11 rows selected.

-------------------------------------------------------------set echo on select deptno, count(*) cnt_per_deptno, (count(*)*100)/nr deptno_percent from emp, (select max(empno) nr from emp) group by deptno, nr order by deptno;

4) Determine if there are histograms available on any column of the EMP table. What do you observe? a) Currently, there are no histograms defined on any column of the EMP table. SQL> SQL> SQL> SQL> 2 3

@check_emp_histogram set echo on select column_name, histogram, num_buckets from user_tab_columns where table_name='EMP';

COLUMN_NAME -----------------------------EMPNO ENAME PHONE DEPTNO

HISTOGRAM NUM_BUCKETS --------------- ----------NONE NONE NONE NONE

SQL> -------------------------------------------------------------set echo on select column_name, histogram, num_buckets from user_tab_columns where table_name='EMP';



SQL>

Practice 7-2: Automatic Statistics Gathering (continued) 5) Determine if you currently have statistics gathered on your EMP table. What do you observe? a) Currently, there are no statistics gathered on your EMP table.

LAST_ANAL SAMPLE_SIZE MON NUM_ROWS BLOCKS TABLE_NAME --------- ----------- --- ---------- ---------- ----------------------------YES EMP SQL> -------------------------------------------------------------set echo on set linesize 200 pagesize 1000 SELECT last_analyzed,sample_size,monitoring,num_rows,blocks,table_name FROM user_tables WHERE table_name = 'EMP';

6) Determine if you currently have statistics gathered on the index created on top of the EMP table. What do you observe? a) Currently, EMP_I1 has no statistics gathered. SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5

@check_index_last_analyzed set echo on set linesize 200 pagesize 1000 SELECT index_name name,num_rows, last_analyzed,distinct_keys,leaf_blocks, avg_leaf_blocks_per_key,join_index FROM user_indexes WHERE table_name = 'EMP';

NAME NUM_ROWS LAST_ANAL DISTINCT_KEYS LEAF_BLOCKS AVG_LEAF_BLOCKS_PER_KEY JOI ------------------------------ ---------- --------- ------------- ---------- ----------------------- --EMP_I1 NO



SQL> @check_table_last_analyzed SQL> set echo on SQL> SQL> set linesize 200 pagesize 1000 SQL> SQL> SELECT last_analyzed,sample_size,monitoring,num_rows,blocks,table_name 2 FROM user_tables 3 WHERE table_name = 'EMP';

Practice 7-2: Automatic Statistics Gathering (continued) SQL> -------------------------------------------------------------set echo on set linesize 200 pagesize 1000

7) Execute the following two statements and determine their execution plans: select count(*), max(empno) from emp where deptno = 9; select count(*), max(empno) from emp where deptno = 10;

What do you observe and why? a) You see that for literal 9, the optimizer decided to use the index whereas for literal 10, the optimizer decided to do TABLE ACCESS FULL. The optimizer determined the correct plans in both cases. This is because dynamic sampling was used, as there were no statistics gathered on both objects. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL>

@check_exec_plans set echo on set linesize 200 pagesize 1000 set autotrace on select count(*), max(empno) from emp where deptno = 9;

COUNT(*) MAX(EMPNO) ---------- ---------10 99

Execution Plan ---------------------------------------------------------Plan hash value: 3184478295 -------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 26 | 2 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 26 | | | | 2 | TABLE ACCESS BY INDEX ROWID| EMP | 10 | 260 | 2 (0)| 00:00:01 |



SELECT index_name name,num_rows, last_analyzed,distinct_keys,leaf_blocks, avg_leaf_blocks_per_key,join_index FROM user_indexes WHERE table_name = 'EMP';

Practice 7-2: Automatic Statistics Gathering (continued) |* 3 | INDEX RANGE SCAN | EMP_I1 | 10 | | 1 (0)| 00:00:01 | -------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------3 - access("DEPTNO"=9)

Statistics ---------------------------------------------------------9 recursive calls 0 db block gets 64 consistent gets 1 physical reads 0 redo size 481 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 1 rows processed SQL> SQL> select count(*), max(empno) from emp where deptno = 10; COUNT(*) MAX(EMPNO) ---------- ---------99900 100000

Execution Plan ---------------------------------------------------------Plan hash value: 2083865914 -------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 26 | 265 (1)| 00:00:03 | | 1 | SORT AGGREGATE | | 1 | 26 | | | |* 2 | TABLE ACCESS FULL| EMP | 86262 | 2190K| 265 (1)| 00:00:03 | -------------------------------------------------------------------------Predicate Information (identified by operation id):




Practice 7-2: Automatic Statistics Gathering (continued) --------------------------------------------------2 - filter("DEPTNO"=10)

Statistics ---------------------------------------------------------7 recursive calls 0 db block gets 871 consistent gets 5 physical reads 0 redo size 482 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 1 rows processed SQL> SQL> set autotrace off SQL> -------------------------------------------------------------set echo on set linesize 200 pagesize 1000 set autotrace on select count(*), max(empno) from emp where deptno = 9; select count(*), max(empno) from emp where deptno = 10; set autotrace off

8) Confirm your assumption from the previous step. SQL> show parameter optimizer_dynamic_sampling NAME TYPE VALUE ------------------------------------ ----------- ----------------------------optimizer_dynamic_sampling integer 2 SQL>

9) Make sure you disable the mechanism found in the previous step. SQL> alter session set optimizer_dynamic_sampling=0; Session altered. SQL>




Practice 7-2: Automatic Statistics Gathering (continued) 10) Perform step 7 again. What do you observe and why? a) Because dynamic sampling is not used, the optimizer cannot use any statistics. It uses default statistics that are not a good choice for the second statement. @check_exec_plans set echo on set linesize 200 pagesize 1000 set autotrace on select count(*), max(empno) from emp where deptno = 9;

COUNT(*) MAX(EMPNO) ---------- ---------10 99

Execution Plan ---------------------------------------------------------Plan hash value: 3184478295 -------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 26 | 5 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 26 | | | | 2 | TABLE ACCESS BY INDEX ROWID| EMP | 714 | 18564 | 5 (0)| 00:00:01 | |* 3 | INDEX RANGE SCAN | EMP_I1 | 286 | | 1 (0)| 00:00:01 | -------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------3 - access("DEPTNO"=9)




SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL>

Practice 7-2: Automatic Statistics Gathering (continued) 0 1


SQL> SQL> select count(*), max(empno) from emp where deptno = 10; COUNT(*) MAX(EMPNO) ---------- ---------99900 100000

-------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 26 | 5 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 26 | | | | 2 | TABLE ACCESS BY INDEX ROWID| EMP | 714 | 18564 | 5 (0)| 00:00:01 | |* 3 | INDEX RANGE SCAN | EMP_I1 | 286 | | 1 (0)| 00:00:01 | -------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------3 - access("DEPTNO"=10)

Statistics ---------------------------------------------------------1 recursive calls 0 db block gets 954 consistent gets 190 physical reads 0 redo size 482 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 1 rows processed SQL> SQL> set autotrace off SQL> --------------------------------------------------------------




Practice 7-2: Automatic Statistics Gathering (continued) set echo on set linesize 200 pagesize 1000 set autotrace on select count(*), max(empno) from emp where deptno = 9; select count(*), max(empno) from emp where deptno = 10; set autotrace off

SQL> alter session set optimizer_dynamic_sampling=2; Session altered. SQL>

12) Set the following wrong statistic values for your EMP table: - Set its number of rows to 10. - Set its number of blocks to 5. SQL> @set_wrong_stats SQL> set echo on SQL> SQL> exec dbms_stats.set_table_stats('AGS','EMP',null,null,null,10,5); PL/SQL procedure successfully completed. SQL> -------------------------------------------------------------set echo on exec dbms_stats.set_table_stats('AGS','EMP',null,null,null,10,5);

13) Check that you modified correctly the statistics of the EMP table. SQL> @check_table_last_analyzed SQL> set echo on SQL> SQL> set linesize 200 pagesize 1000 SQL> SQL> SELECT last_analyzed,sample_size,monitoring,num_rows,blocks,table_name 2 FROM user_tables 3 WHERE table_name = 'EMP'; LAST_ANAL SAMPLE_SIZE MON NUM_ROWS BLOCKS TABLE_NAME --------- ----------- --- ---------- ---------- -----------------------------



11) Reset dynamic sampling as it was at the beginning of this lab.

Practice 7-2: Automatic Statistics Gathering (continued) 07-APR-08

2000 YES

10

5 EMP

SQL> -------------------------------------------------------------set echo on set linesize 200 pagesize 1000

14) Perform step 7 again. What do you observe and why? a) Because there are statistics defined on the EMP table, the optimizer uses them, and not dynamic sampling. However, because the statistics are incorrect, the generated plans are also incorrect, at least for the second statement. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL>


COUNT(*) MAX(EMPNO) ---------- ---------10 99

Execution Plan ---------------------------------------------------------Plan hash value: 3184478295 -------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 26 | 2 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 26 | | | | 2 | TABLE ACCESS BY INDEX ROWID| EMP | 1 | 26 | 2 (0)| 00:00:01 | |* 3 | INDEX RANGE SCAN | EMP_I1 | 1 | | 1 (0)| 00:00:01 | --------------------------------------------------------------------------------------



SELECT last_analyzed,sample_size,monitoring,num_rows,blocks,table_name FROM user_tables WHERE table_name = 'EMP';

Practice 7-2: Automatic Statistics Gathering (continued) Predicate Information (identified by operation id): ---------------------------------------------------


Execution Plan ---------------------------------------------------------Plan hash value: 3184478295 -------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 26 | 2 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 26 | | | | 2 | TABLE ACCESS BY INDEX ROWID| EMP | 1 | 26 | 2 (0)| 00:00:01 | |* 3 | INDEX RANGE SCAN | EMP_I1 | 1 | | 1 (0)| 00:00:01 | -------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------3 - access("DEPTNO"=10)

Statistics ----------------------------------------------------------



3 - access("DEPTNO"=9)

Practice 7-2: Automatic Statistics Gathering (continued) 0 0 805 0 0 482 420 2 0 0 1

recursive calls db block gets consistent gets physical reads redo size bytes sent via SQL*Net to client bytes received via SQL*Net from client SQL*Net roundtrips to/from client sorts (memory) sorts (disk) rows processed

-------------------------------------------------------------set echo on set linesize 200 pagesize 1000 set autotrace on select count(*), max(empno) from emp where deptno = 9; select count(*), max(empno) from emp where deptno = 10; set autotrace off

15) Make sure you manually gather statistics on your EMP table and its corresponding index. SQL> @gather_stats_manually SQL> set echo on SQL> SQL> exec dbms_stats.gather_table_stats('AGS', 'EMP', cascade => true); PL/SQL procedure successfully completed. SQL> -------------------------------------------------------------set echo on exec dbms_stats.gather_table_stats('AGS', 'EMP', cascade => true);

16) Make sure statistics were gathered on your objects. SQL> @check_table_last_analyzed SQL> set echo on SQL> SQL> set linesize 200 pagesize 1000



SQL> SQL> set autotrace off SQL>

Practice 7-2: Automatic Statistics Gathering (continued) SQL> SQL> SELECT last_analyzed,sample_size,monitoring,num_rows,blocks,table_name 2 FROM user_tables 3 WHERE table_name = 'EMP'; LAST_ANAL SAMPLE_SIZE MON NUM_ROWS BLOCKS TABLE_NAME --------- ----------- --- ---------- ---------- ----------------------------07-APR-08 100000 YES 100000 874 EMP


NAME NUM_ROWS LAST_ANAL DISTINCT_KEYS LEAF_BLOCKS AVG_LEAF_BLOCKS_PER_KEY JOI ------------------------------ ---------- --------- ------------- ---------- ----------------------- --EMP_I1 100000 07-APR-08 11 196 17 NO SQL> SQL> SQL> SQL> SQL> 2 3



HISTOGRAM NUM_BUCKETS --------------- ----------NONE 1 NONE 1 NONE 1 FREQUENCY 7

SQL>

17) Perform step 7 again. What do you observe and why? a) Because statistics were correctly gathered on both objects, the optimizer is able to use correct execution plans for both statements. SQL> @check_exec_plans SQL> set echo on SQL> SQL> set linesize 200 pagesize 1000



SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5

Practice 7-2: Automatic Statistics Gathering (continued) SQL> SQL> set autotrace on SQL> SQL> select count(*), max(empno) from emp where deptno = 9; COUNT(*) MAX(EMPNO) ---------- ---------10 99

-------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 8 | 2 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 8 | | | | 2 | TABLE ACCESS BY INDEX ROWID| EMP | 18 | 144 | 2 (0)| 00:00:01 | |* 3 | INDEX RANGE SCAN | EMP_I1 | 18 | | 1 (0)| 00:00:01 | -------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------3 - access("DEPTNO"=9)





Practice 7-2: Automatic Statistics Gathering (continued)

-------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 8 | 265 (1)| 00:00:03 | | 1 | SORT AGGREGATE | | 1 | 8 | | | |* 2 | TABLE ACCESS FULL| EMP | 99864 | 780K| 265 (1)| 00:00:03 | -------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - filter("DEPTNO"=10)

Statistics ---------------------------------------------------------0 recursive calls 0 db block gets 805 consistent gets 0 physical reads 0 redo size 482 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 1 rows processed SQL> SQL> set autotrace off SQL>

18) Ensure you delete all statistics previously generated on your objects. SQL> @delete_stats SQL> set echo on SQL> SQL> exec dbms_stats.delete_schema_stats('AGS'); PL/SQL procedure successfully completed. SQL> -------------------------------------------------------------set echo on




Practice 7-2: Automatic Statistics Gathering (continued) exec dbms_stats.delete_schema_stats('AGS');

SQL> @check_table_last_analyzed SQL> set echo on SQL> SQL> set linesize 200 pagesize 1000 SQL> SQL> SELECT last_analyzed,sample_size,monitoring,num_rows,blocks,table_name 2 FROM user_tables 3 WHERE table_name = 'EMP'; LAST_ANAL SAMPLE_SIZE MON NUM_ROWS BLOCKS TABLE_NAME --------- ----------- --- ---------- ---------- ----------------------------YES EMP SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5


NAME NUM_ROWS LAST_ANAL DISTINCT_KEYS LEAF_BLOCKS AVG_LEAF_BLOCKS_PER_KEY JOI ------------------------------ ---------- --------- ------------- ---------- ----------------------- --EMP_I1 NO SQL> SQL> SQL> SQL> SQL> 2 3



HISTOGRAM NUM_BUCKETS --------------- ----------NONE NONE NONE NONE

SQL>



19) Verify that you no longer have statistics gathered on both objects.

Practice 7-2: Automatic Statistics Gathering (continued) 20) How would you determine the list of automated tasks that exist on your database? a) You can use Enterprise Manager Database Control by navigating to the Automated Maintenance Tasks page (Home > Server> Automated Maintenance Tasks). On the Automated Maintenance Tasks page, you can see the three automated tasks implemented by default on your database. b) Another possibility is to use the DBA_AUTOTASK_TASK table as shown by the following statement:

TASK_NAME ---------------------------------------------------------------gather_stats_prog auto_space_advisor_prog AUTO_SQL_TUNING_PROG SQL>

21) Exit from your SQL*Plus session. SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Automatic_Gather_Stats]$

22) You now want to observe the effects of the automatic statistics-gathering feature of your database. However, you do not want to wait until the database automatically opens the next maintenance window. So from your terminal session, execute the run_ags.sh script. This script forces the execution of the automatic statisticsgathering task. [oracle@edrsr33p1-orcl Automatic_Gather_Stats]$ ./run_ags.sh SQL*Plus: Release 11.1.0.6.0 - Production on Mon Apr 7 16:00:03 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> exec dbms_workload_repository.create_snapshot; PL/SQL procedure successfully completed. SQL> SQL> variable window varchar2(20); SQL> SQL> begin



SQL> select task_name from dba_autotask_task;

Practice 7-2: Automatic Statistics Gathering (continued) 2 select upper(to_char(sysdate,'fmday'))||'_WINDOW' into :window from dual; 3 end; 4 / PL/SQL procedure successfully completed. SQL> SQL> print window;

SQL> SQL> -SQL> -- Open the corresponding maintenance window, but with other clients disabled SQL> -SQL> SQL> alter system set "_enable_automatic_maintenance"=1 2 / System altered. SQL> SQL> exec dbms_auto_task_admin.disable( > 'auto space advisor', null, :window); PL/SQL procedure successfully completed. SQL> SQL> exec dbms_auto_task_admin.disable( > 'sql tuning advisor', null, :window); PL/SQL procedure successfully completed. SQL> SQL> SQL> exec dbms_scheduler.open_window(:window, null, true); PL/SQL procedure successfully completed. SQL> SQL> -SQL> -- Close the maintenance window when auto optimizer stats collection is done SQL> -SQL> SQL> SQL> exec dbms_lock.sleep(120); PL/SQL procedure successfully completed. SQL> SQL> exec dbms_scheduler.close_window(:window);



WINDOW -------------------------------MONDAY_WINDOW

Practice 7-2: Automatic Statistics Gathering (continued) PL/SQL procedure successfully completed. SQL> SQL> SQL> alter system set "_enable_automatic_maintenance"=0 2 /

SQL> SQL> -SQL> -- Re-enable the other guys so they look like they are enabled in EM. SQL> -- Still they will be disabled because we have set the underscore. SQL> -SQL> SQL> exec dbms_auto_task_admin.enable( > 'auto space advisor', null, :window); PL/SQL procedure successfully completed. SQL> SQL> exec dbms_auto_task_admin.enable( > 'sql tuning advisor', null, :window); PL/SQL procedure successfully completed. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Automatic_Gather_Stats]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Automatic_Gather_Stats export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @run_ags.sql -------------------------------------------------------------set echo on exec dbms_workload_repository.create_snapshot;



System altered.

Practice 7-2: Automatic Statistics Gathering (continued) variable window varchar2(20); begin select upper(to_char(sysdate,'fmday'))||'_WINDOW' into :window from dual; end; / print window;

alter system set "_enable_automatic_maintenance"=1 / exec dbms_auto_task_admin.disable( 'auto space advisor', null, :window); exec dbms_auto_task_admin.disable( 'sql tuning advisor', null, :window);

exec dbms_scheduler.open_window(:window, null, true); --- Close the maintenance window when auto optimizer stats collection is done --

exec dbms_lock.sleep(120); exec dbms_scheduler.close_window(:window);

alter system set "_enable_automatic_maintenance"=0 / --- Re-enable the other guys so they look like they are enabled in EM. -- Still they will be disabled because we have set the underscore. -exec dbms_auto_task_admin.enable( 'auto space advisor', null, :window); exec dbms_auto_task_admin.enable( 'sql tuning advisor', null, :window); exit;



--- Open the corresponding maintenance window, but with other clients disabled --

Practice 7-2: Automatic Statistics Gathering (continued) 23) Connect again as the AGS user from a SQL*Plus session. [oracle@edrsr33p1-orcl Automatic_Gather_Stats]$ sqlplus ags/ags SQL*Plus: Release 11.1.0.6.0 - Production on Mon Apr 7 16:02:44 2008 Copyright (c) 1982, 2007, Oracle.


SQL>

24) View the statistics of your objects. What do you observe and why? a) The statistics were automatically gathered by the database during the maintenance window. You can also see this directly from the Automated Maintenance Tasks page in Enterprise Manager. The important thing is that the database automatically gathered the right statistics and histograms. Depending on your environment, you may see different sample sizes. SQL> @check_table_last_analyzed SQL> SQL> set linesize 200 pagesize 1000 SQL> SQL> SELECT last_analyzed,sample_size,monitoring,num_rows,blocks,table_name 2 FROM user_tables 3 WHERE table_name = 'EMP'; LAST_ANAL SAMPLE_SIZE MON NUM_ROWS BLOCKS TABLE_NAME --------- ----------- --- ---------- ---------- ----------------------------07-APR-08 100000 YES 100000 874 EMP SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5


NAME NUM_ROWS LAST_ANAL DISTINCT_KEYS LEAF_BLOCKS AVG_LEAF_BLOCKS_PER_KEY JOI ------------------------------ ---------- --------- ------------- ---------- ----------------------- --EMP_I1 100000 07-APR-08 11 196 17 NO




Practice 7-2: Automatic Statistics Gathering (continued) @check_emp_histogram set echo on select column_name, histogram, num_buckets from user_tab_columns where table_name='EMP';


HISTOGRAM NUM_BUCKETS --------------- ----------NONE 1 NONE 1 NONE 1 FREQUENCY 5

SQL>

25) Perform step 7 again. What do you observe and why? a) The optimizer can make the right decisions for both statements. This is because of the statistics that were automatically gathered by the database previously. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL>


COUNT(*) MAX(EMPNO) ---------- ---------10 99

Execution Plan ---------------------------------------------------------Plan hash value: 3184478295 -------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 8 | 2 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 8 | | | | 2 | TABLE ACCESS BY INDEX ROWID| EMP | 9 | 72 | 2 (0)| 00:00:01 | |* 3 | INDEX RANGE SCAN | EMP_I1 | 9 | | 1 (0)| 00:00:01 | --------------------------------------------------------------------------------------



SQL> SQL> SQL> SQL> SQL> 2 3

Practice 7-2: Automatic Statistics Gathering (continued) Predicate Information (identified by operation id): ---------------------------------------------------


Execution Plan ---------------------------------------------------------Plan hash value: 2083865914 -------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 8 | 265 (1)| 00:00:03 | | 1 | SORT AGGREGATE | | 1 | 8 | | | |* 2 | TABLE ACCESS FULL| EMP | 99863 | 780K| 265 (1)| 00:00:03 | -------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - filter("DEPTNO"=10)

Statistics ---------------------------------------------------------0 recursive calls 0 db block gets



3 - access("DEPTNO"=9)

Practice 7-2: Automatic Statistics Gathering (continued) 805 0 0 482 420 2 0 0 1

consistent gets physical reads redo size bytes sent via SQL*Net to client bytes received via SQL*Net from client SQL*Net roundtrips to/from client sorts (memory) sorts (disk) rows processed

SQL> SQL> set autotrace off SQL>

SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Automatic_Gather_Stats]$

27) From your terminal window, clean up your environment by executing the ags_cleanup.sh script. [oracle@edrsr33p1-orcl Automatic_Gather_Stats]$ ./ags_cleanup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Mon Apr 7 16:03:37 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> drop user ags cascade; User dropped. SQL> SQL> alter system set "_enable_automatic_maintenance"=1; System altered. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Automatic_Gather_Stats]$ --------------------------------------------------------------




Practice 7-2: Automatic Statistics Gathering (continued) #!/bin/bash cd /home/oracle/solutions/Automatic_Gather_Stats export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin

-------------------------------------------------------------set echo on drop user ags cascade; alter system set "_enable_automatic_maintenance"=1; exit;



sqlplus / as sysdba @ags_cleanup.sql




Practice 8-1: Understanding Adaptive Cusrsor Sharing In this practice, you experiment with bind variable peeking and adaptive cursor sharing. 1) Connected to a terminal session as the oracle user, execute the acs_setup.sh script to set up the environment used for this lab. You can locate this script in your $HOME/solutions/Adaptive_Cursor_Sharing directory. [oracle@edrsr33p1-orcl ~]$ cd solutions/Adaptive_Cursor_Sharing [oracle@edrsr33p1-orcl Adaptive_Cursor_Sharing]$ ./acs_setup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Fri Mar 28 16:54:36 2008 All rights reserved.

Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> drop user acs cascade; drop user acs cascade * ERROR at line 1: ORA-01918: user 'ACS' does not exist

SQL> SQL> create user acs identified by acs default tablespace users temporary tablespace temp; User created. SQL> SQL> grant dba, connect to acs; Grant succeeded. SQL> SQL> connect acs/acs Connected. SQL> SQL> drop table emp purge; drop table emp purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> SQL> create table emp 2 ( 3 empno number,




Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) 4 5 6 7

ename phone deptno );

varchar2(20), varchar2(20), number

SQL> SQL> SQL> insert into emp 2 with tdata as 3 (select rownum empno 4 from all_objects 5 where rownum <= 1000) 6 select rownum, 7 dbms_random.string ('u', 20), 8 dbms_random.string ('u', 20), 9 case 10 when rownum/100000 <= 0.001 then mod(rownum, 10) 11 else 10 12 end 13 from tdata a, tdata b 14 where rownum <= 100000; 100000 rows created. SQL> SQL> create index emp_i1 on emp(deptno); Index created. SQL> SQL> exec dbms_stats.gather_table_stats(null, 'EMP', METHOD_OPT => 'FOR COLUMNS DEPTNO SIZE 10', CASCADE => TRUE); PL/SQL procedure successfully completed. SQL> SQL> alter system flush shared_pool; System altered. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Adaptive_Cursor_Sharing]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Adaptive_Cursor_Sharing



Table created.

Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @acs_setup.sql --------------------------------------------------------------

drop user acs cascade; create user acs identified by acs default tablespace users temporary tablespace temp; grant dba, connect to acs; connect acs/acs drop table emp purge; create table emp ( empno number, ename varchar2(20), phone varchar2(20), deptno number ); insert into emp with tdata as (select rownum empno from all_objects where rownum <= 1000) select rownum, dbms_random.string ('u', 20), dbms_random.string ('u', 20), case when rownum/100000 <= 0.001 then mod(rownum, 10) else 10 end from tdata a, tdata b where rownum <= 100000; create index emp_i1 on emp(deptno); exec dbms_stats.gather_table_stats(null, 'EMP', METHOD_OPT => 'FOR COLUMNS DEPTNO SIZE 10', CASCADE => TRUE); alter system flush shared_pool; exit;



set echo on

Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) 2) In your terminal session, connect to the SQL*Plus session as the ACS user. Ensure that you stay connected to the same SQL*Plus session until the end of this lab. After you get connected, identify the columns of the EMP table that have histograms. a) Only the DEPTNO column has a 10 buckets histogram. [oracle@edrsr33p1-orcl Adaptive_Cursor_Sharing]$ sqlplus acs/acs SQL*Plus: Release 11.1.0.6.0 - Production on Fri Mar 28 16:54:49 2008 All rights reserved.

Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> SQL> 2 3

@check_emp_histogram select column_name, histogram, num_buckets from user_tab_columns where table_name='EMP';


HISTOGRAM NUM_BUCKETS --------------- ----------NONE NONE NONE HEIGHT BALANCED 10

SQL> -------------------------------------------------------------set echo on select column_name, histogram, num_buckets from user_tab_columns where table_name='EMP';

3) Determine the distribution of all the distinct values found in the DEPTNO column of the EMP table. What do you find? a) Values distribution is uniform for all of them (0.01%) except for value 10 (99.9%). This is typical of what is called data skew. SQL> @show_deptno_distribution SQL> set echo on SQL> SQL> select deptno, count(*) cnt_per_deptno, (count(*)*100)/nr deptno_percent




Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) from emp, (select max(empno) nr from emp) group by deptno, nr order by deptno;

DEPTNO CNT_PER_DEPTNO DEPTNO_PERCENT ---------- -------------- -------------0 10 .01 1 10 .01 2 10 .01 3 10 .01 4 10 .01 5 10 .01 6 10 .01 7 10 .01 8 10 .01 9 10 .01 10 99900 99.9 11 rows selected. SQL> -------------------------------------------------------------set echo on select deptno, count(*) cnt_per_deptno, (count(*)*100)/nr deptno_percent from emp, (select max(empno) nr from emp) group by deptno, nr order by deptno;

4) Before you study the adaptive cursor sharing feature, disable its functionality by setting the OPTIMIZER_FEATURES_ENABLE session parameter back to 10.2.0.1. After this is done, ensure that you execute the following command in your SQL*Plus session: set lines 200 pages 10000. This is used in the lab to print execution plans correctly. SQL> alter session set optimizer_features_enable="10.2.0.1"; Session altered. SQL> set lines 200 pages 10000

5) Determine the execution plan for the following statement: select /*ACS_L9*/ count(*), max(empno) from emp where deptno = 9; What do you notice and why? a) The optimizer uses an index range scan because value 9 is very selective. Oracle Database 11g: SQL Tuning Workshop A - 245


2 3 4 5

Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) SQL> SQL> SQL> SQL> 2 3

@select_deptno_literal_9 set echo on select /*ACS_L9*/ count(*), max(empno) from emp where deptno = 9;

SQL> SQL> @show_latest_exec_plan SQL> set echo on SQL> SQL> select * from table(dbms_xplan.display_cursor); PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID 64ngy4j55d1z5, child number 0 ------------------------------------select /*ACS_L9*/ count(*), max(empno) from emp where deptno = 9 Plan hash value: 3184478295 -------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | | | 2 (100)| | | 1 | SORT AGGREGATE | | 1 | 16 | | | | 2 | TABLE ACCESS BY INDEX ROWID| EMP | 12 | 192 | 2 (0)| 00:00:01 | |* 3 | INDEX RANGE SCAN | EMP_I1 | 12 | | 1 (0)| 00:00:01 | -------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------3 - access("DEPTNO"=9)

20 rows selected. SQL> --------------------------------------------------------------



COUNT(*) MAX(EMPNO) ---------- ---------10 99

Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) set echo on select /*ACS_L9*/ count(*), max(empno) from emp where deptno = 9;

6) Determine the execution plan for the following statement: select /*ACS_L10*/ count(*), max(empno) from emp where deptno = 10; a) The optimizer uses a full table scan because value 10 is not a selective value. SQL> SQL> SQL> SQL> 2 3

@select_deptno_literal_10 set echo on select /*ACS_L10*/ count(*), max(empno) from emp where deptno = 10;

COUNT(*) MAX(EMPNO) ---------- ---------99900 100000 SQL> SQL> @show_latest_exec_plan SQL> set echo on SQL> SQL> select * from table(dbms_xplan.display_cursor); PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID 3232j5gkp2u5h, child number 0 ------------------------------------select /*ACS_L10*/ count(*), max(empno) from emp where deptno = 10 Plan hash value: 2083865914 -------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------| 0 | SELECT STATEMENT | | | | 240 (100)| | | 1 | SORT AGGREGATE | | 1 | 16 | | | |* 2 | TABLE ACCESS FULL| EMP | 95000 | 1484K| 240 (1)| 00:00:03 |



What do you notice and why?

Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) -------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - filter("DEPTNO"=10)

19 rows selected. SQL>

set echo on select /*ACS_L10*/ count(*), max(empno) from emp where deptno = 10;

7) Define a bind variable called DEPTNO in your SQL*Plus session, set it to value 9, and execute the following query, and determine its execution plan: select /*ACS_1*/ count(*), max(empno) from emp where deptno = :deptno; What do you notice and why? a) Because the optimizer uses bind peeking the first time you execute a statement with a bind variable, and because for this first execution, value 9 is used, the execution plan with index access is used. SQL> variable deptno number; SQL> exec :deptno := 9 PL/SQL procedure successfully completed. SQL> SQL> SQL> SQL> 2 3

@select_deptno_bind set echo on select /*ACS_1*/ count(*), max(empno) from emp where deptno = :deptno;

COUNT(*) MAX(EMPNO) ---------- ---------10 99 SQL> SQL> @show_latest_exec_plan SQL> set echo on SQL> SQL> select * from table(dbms_xplan.display_cursor);



--------------------------------------------------------------

Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID 272gr4hapc9w1, child number 0 ------------------------------------select /*ACS_1*/ count(*), max(empno) from emp where deptno = :deptno

-------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | | | 2 (100)| | | 1 | SORT AGGREGATE | | 1 | 16 | | | | 2 | TABLE ACCESS BY INDEX ROWID| EMP | 12 | 192 | 2 (0)| 00:00:01 | |* 3 | INDEX RANGE SCAN | EMP_I1 | 12 | | 1 (0)| 00:00:01 | -------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------3 - access("DEPTNO"=:DEPTNO)

20 rows selected. SQL> -------------------------------------------------------------set echo on select /*ACS_1*/ count(*), max(empno) from emp where deptno = :deptno; -------------------------------------------------------------set echo on select * from table(dbms_xplan.display_cursor);




Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) 8) Determine the execution statistics in terms of child cursors, executions, and buffer gets for the previously executed statement. What do you observe? a) In V$SQL, only one child cursor exists, and it has been executed only once (first time ever in this case). Also, the number of buffer gets is small due to the efficient access path that was used. @show_latest_exec_stats set echo on select child_number, executions, buffer_gets from v$sql where sql_text like 'select /*ACS_1%';

CHILD_NUMBER EXECUTIONS BUFFER_GETS ------------ ---------- ----------0 1 3 SQL> -------------------------------------------------------------set echo on select child_number, executions, buffer_gets from v$sql where sql_text like 'select /*ACS_1%';

9) Perform steps 7 and 8 again, but this time using 10 as the bind value for DEPTNO. What do you observe and why? a) The execution plan is identical. The index path is used although value 10 is not selective. This is because bind peeking only operates the first time you execute your statement. Looking at V$SQL, you can clearly see that there is still only one child cursor associated with your statement. However, this time, the number of buffer gets was raised significantly due to the full table scan. SQL> exec :deptno := 10 PL/SQL procedure successfully completed. SQL> SQL> SQL> SQL> 2 3


COUNT(*) MAX(EMPNO) ---------- ---------99900 100000 SQL> SQL> @show_latest_exec_plan



SQL> SQL> SQL> SQL> 2 3

Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) SQL> set echo on SQL> SQL> select * from table(dbms_xplan.display_cursor); PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID 272gr4hapc9w1, child number 0 ------------------------------------select /*ACS_1*/ count(*), max(empno) from emp where deptno = :deptno


20 rows selected. SQL> SQL> SQL> SQL> SQL> 2 3

@show_latest_exec_stats set echo on select child_number, executions, buffer_gets from v$sql where sql_text like 'select /*ACS_1%';

CHILD_NUMBER EXECUTIONS BUFFER_GETS ------------ ---------- ----------0 2 957 SQL>

10) Before the next step, flush your shared pool to make sure you wipe out all cursor’s information. Oracle Database 11g: SQL Tuning Workshop A - 251



Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) SQL> alter system flush shared_pool; System altered. SQL>

11) Perform step 9 again. What do you observe and why? a) The execution plan is a full table scan because you used value 10 as your first bind value. There is only one child cursor that is created so far to handle your statement.

PL/SQL procedure successfully completed. SQL> SQL> SQL> SQL> 2 3


COUNT(*) MAX(EMPNO) ---------- ---------99900 100000 SQL> SQL> @show_latest_exec_plan SQL> set echo on SQL> SQL> select * from table(dbms_xplan.display_cursor); PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID 272gr4hapc9w1, child number 0 ------------------------------------select /*ACS_1*/ count(*), max(empno) from emp where deptno = :deptno Plan hash value: 2083865914 -------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------| 0 | SELECT STATEMENT | | | | 240 (100)| | | 1 | SORT AGGREGATE | | 1 | 16 | | | |* 2 | TABLE ACCESS FULL| EMP | 95000 | 1484K| 240 (1)| 00:00:03 |



SQL> exec :deptno := 10

Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) -------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - filter("DEPTNO"=:DEPTNO)

19 rows selected.



12) Perform step 9 again, but this time use 9 as your bind value. What do you observe and why? a) Although value 9 is very selective, a full table scan is still used. This is because the second time you execute your statement, bind peeking is not done. So you continue to use the same child cursor. SQL> exec :deptno := 9 PL/SQL procedure successfully completed. SQL> SQL> SQL> SQL> 2 3


COUNT(*) MAX(EMPNO) ---------- ---------10 99 SQL> SQL> @show_latest_exec_plan SQL> set echo on SQL> SQL> select * from table(dbms_xplan.display_cursor); PLAN_TABLE_OUTPUT




Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID 272gr4hapc9w1, child number 0 ------------------------------------select /*ACS_1*/ count(*), max(empno) from emp where deptno = :deptno

-------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------| 0 | SELECT STATEMENT | | | | 240 (100)| | | 1 | SORT AGGREGATE | | 1 | 16 | | | |* 2 | TABLE ACCESS FULL| EMP | 95000 | 1484K| 240 (1)| 00:00:03 | -------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - filter("DEPTNO"=:DEPTNO)




13) Before the next step, reset your session to use adaptive cursor sharing, and ensure that you flush your shared pool again. SQL> alter session set optimizer_features_enable="11.1.0.6"; Session altered. SQL> alter system flush shared_pool;




Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) System altered. SQL>

14) Perform step 12 again. What do you observe, and why? a) Because this is the first time you execute the statement, bind peeking is used, and because value 9 is very selective, the index path is used. Only one child cursor is used to handle this statement. SQL> exec :deptno := 9

SQL> SQL> SQL> SQL> 2 3


COUNT(*) MAX(EMPNO) ---------- ---------10 99 SQL> SQL> @show_latest_exec_plan SQL> set echo on SQL> SQL> select * from table(dbms_xplan.display_cursor); PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID 272gr4hapc9w1, child number 0 ------------------------------------select /*ACS_1*/ count(*), max(empno) from emp where deptno = :deptno Plan hash value: 3184478295 -------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | | | 2 (100)| | | 1 | SORT AGGREGATE | | 1 | 16 | | | | 2 | TABLE ACCESS BY INDEX ROWID| EMP | 1 | 16 | 2 (0)| 00:00:01 | |* 3 | INDEX RANGE SCAN | EMP_I1 | 1 | | 1 (0)| 00:00:01 |




Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) -------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------3 - access("DEPTNO"=:DEPTNO)

20 rows selected.



15) Perform step 14 again, but this time using value 10 as your bind value. What do you observe and why? a) Although value 10 is not selective, the same index path as in the previous step is used. Only one child cursor is currently needed to represent your statement. SQL> exec :deptno := 10 PL/SQL procedure successfully completed. SQL> SQL> SQL> SQL> 2 3


COUNT(*) MAX(EMPNO) ---------- ---------99900 100000 SQL> SQL> @show_latest_exec_plan SQL> set echo on SQL> SQL> select * from table(dbms_xplan.display_cursor); PLAN_TABLE_OUTPUT ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------




Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) SQL_ID 272gr4hapc9w1, child number 0 ------------------------------------select /*ACS_1*/ count(*), max(empno) from emp where deptno = :deptno





16) Perform step 15 again. What do you observe and why? a) Because you now use adaptive cursor sharing, the system realizes that you benefit from another child cursor for handling your statement. This time, a full table access path is used to better handle your statement. SQL> exec :deptno := 10 PL/SQL procedure successfully completed.




Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) SQL> SQL> SQL> SQL> 2 3


SQL> SQL> @show_latest_exec_plan SQL> set echo on SQL> SQL> select * from table(dbms_xplan.display_cursor); PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID 272gr4hapc9w1, child number 1 ------------------------------------select /*ACS_1*/ count(*), max(empno) from emp where deptno = :deptno Plan hash value: 2083865914 -------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------| 0 | SELECT STATEMENT | | | | 240 (100)| | | 1 | SORT AGGREGATE | | 1 | 16 | | | |* 2 | TABLE ACCESS FULL| EMP | 95000 | 1484K| 240 (1)| 00:00:03 | -------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------2 - filter("DEPTNO"=:DEPTNO)

19 rows selected. SQL> SQL> @show_latest_exec_stats SQL> set echo on SQL> SQL> select child_number, executions, buffer_gets



COUNT(*) MAX(EMPNO) ---------- ---------99900 100000

Practice 8-1: Understanding Adaptive Cusrsor Sharing (continued) 2 3

from v$sql where sql_text like 'select /*ACS_1%';

CHILD_NUMBER EXECUTIONS BUFFER_GETS ------------ ---------- ----------0 2 1008 1 1 821 SQL>

SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Adaptive_Cursor_Sharing]$ ./acs_cleanup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Fri Mar 28 16:59:18 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> drop user acs cascade; User dropped. SQL> SQL> alter system flush shared_pool; System altered. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Adaptive_Cursor_Sharing]$



17) Exit your SQL*Plus session, and execute the acs_cleanup.sh script to clean up your environment.

Practice 8-2: Understanding CURSOR_SHARING In this practice, you investigate the use of the CURSOR_SHARING initialization parameter. 1) You can find all the necessary scripts for this lab in your $HOME/solutions/Cursor_Sharing directory. First, you must set up the environment for this lab by executing the cs_setup.sh script from a terminal session connected as the oracle user. This script creates a new user called CS and the EMP table used throughout this lab.

SQL*Plus: Release 11.1.0.6.0 - Production on Mon Mar 31 14:10:59 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> drop user cs cascade; User dropped. SQL> SQL> create user cs identified by cs default tablespace users temporary tablespace temp; User created. SQL> SQL> grant dba, connect to cs; Grant succeeded. SQL> SQL> connect cs/cs Connected. SQL> SQL> drop table emp purge; drop table emp purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> SQL> create table emp



[oracle@edrsr33p1-orcl ~]$ cd solutions/Cursor_Sharing [oracle@edrsr33p1-orcl Cursor_Sharing]$ [oracle@edrsr33p1-orcl Cursor_Sharing]$ ./cs_setup.sh

Practice 8-2: Understanding CURSOR_SHARING (continued) 2 3 4 5 6 7

( empno ename phone deptno );

number, varchar2(20), varchar2(20), number

SQL> SQL> SQL> insert into emp 2 with tdata as 3 (select rownum empno 4 from all_objects 5 where rownum <= 1000) 6 select rownum, 7 dbms_random.string ('u', 20), 8 dbms_random.string ('u', 20), 9 case 10 when rownum/100000 <= 0.001 then mod(rownum, 10) 11 else 10 12 end 13 from tdata a, tdata b 14 where rownum <= 100000; 100000 rows created. SQL> SQL> create index emp_i1 on emp(deptno); Index created. SQL> SQL> execute dbms_stats.gather_table_stats(null, 'EMP', cascade => true); PL/SQL procedure successfully completed. SQL> SQL> alter system flush shared_pool; System altered. SQL> SQL> connect / as sysdba Connected. SQL> SQL> shutdown immediate; Database closed. Database dismounted. ORACLE instance shut down. SQL> SQL> startup; ORACLE instance started.



Table created.

Practice 8-2: Understanding CURSOR_SHARING (continued)

-------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Cursor_Sharing export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @cs_setup.sql -------------------------------------------------------------set echo on drop user cs cascade; create user cs identified by cs default tablespace users temporary tablespace temp; grant dba, connect to cs; connect cs/cs drop table emp purge; create table emp ( empno number, ename varchar2(20), phone varchar2(20), deptno number );

insert into emp with tdata as



Total System Global Area 845348864 bytes Fixed Size 1303188 bytes Variable Size 541068652 bytes Database Buffers 297795584 bytes Redo Buffers 5181440 bytes Database mounted. Database opened. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Cursor_Sharing]$

Practice 8-2: Understanding CURSOR_SHARING (continued) (select rownum empno from all_objects where rownum <= 1000) select rownum, dbms_random.string ('u', 20), dbms_random.string ('u', 20), case when rownum/100000 <= 0.001 then mod(rownum, 10) else 10 end from tdata a, tdata b where rownum <= 100000;

execute dbms_stats.gather_table_stats(null, 'EMP', cascade => true); alter system flush shared_pool; connect / as sysdba shutdown immediate; startup; exit;

2) From the same terminal session, connect as the CS user in the SQL*Plus session, and stay connected to that session until the end of this lab. For formatting reasons, after you have connected in the SQL*Plus session, execute the following command: set linesize 200 pagesize 1000 [oracle@edrsr33p1-orcl Cursor_Sharing]$ sqlplus cs/cs SQL*Plus: Release 11.1.0.6.0 - Production on Mon Mar 31 14:11:38 2008 Copyright (c) 1982, 2007, Oracle.



SQL> set linesize 200 pagesize 1000 SQL>

3) Check the existence of histograms on the columns of the EMP table, and then determine the data distribution in the DEPTNO column of the EMP table. What do you observe?



create index emp_i1 on emp(deptno);

Practice 8-2: Understanding CURSOR_SHARING (continued) a) Currently, there are no histograms created on the columns of the EMP table. Also, it is clear that you have data skew in the DEPTNO column. Value 10 repeats most of the time (99.9%) whereas all other values only repeat 0.01%. @check_emp_histogram select column_name, histogram, num_buckets from user_tab_columns where table_name='EMP';


HISTOGRAM NUM_BUCKETS --------------- ----------NONE 1 NONE 1 NONE 1 NONE 1

SQL> SQL> @show_deptno_distribution SQL> set echo on SQL> SQL> select deptno, count(*) cnt_per_deptno, (count(*)*100)/nr deptno_percent 2 from emp, (select max(empno) nr 3 from emp) 4 group by deptno, nr 5 order by deptno; DEPTNO CNT_PER_DEPTNO DEPTNO_PERCENT ---------- -------------- -------------0 10 .01 1 10 .01 2 10 .01 3 10 .01 4 10 .01 5 10 .01 6 10 .01 7 10 .01 8 10 .01 9 10 .01 10 99900 99.9 11 rows selected. SQL> -------------------------------------------------------------set echo on select column_name, histogram, num_buckets from user_tab_columns where table_name='EMP'; -------------------------------------------------------------set echo on



SQL> SQL> SQL> 2 3

Practice 8-2: Understanding CURSOR_SHARING (continued) select deptno, count(*) cnt_per_deptno, (count(*)*100)/nr deptno_percent from emp, (select max(empno) nr from emp) group by deptno, nr order by deptno;

4) Before you continue, ensure that you flush your shared pool. SQL> alter system flush shared_pool;

SQL>

5) How would you force your SQL*Plus session to automatically replace statement literals with bind variables to make sure the same cursor is used independently of the literal values? SQL> alter session set cursor_sharing = force; Session altered. SQL>

6) From the same SQL*Plus session, execute the following two queries, and then determine how many cursors are generated to handle these two statements, and what execution plans were used. What do you observe and why? select /*CS*/ count(*), max(empno) from emp where deptno = 9; select /*CS*/ count(*), max(empno) from emp where deptno = 10;

a) Because of the previous step, literal values are replaced with bind variables. The FORCE option forces the system to share only one child cursor in this case and use the exact same execution plan (index range scan). SQL> @select_deptno_literal_9 SQL> set echo on SQL> SQL> select /*CS*/ count(*), max(empno) from emp where deptno = 9; COUNT(*) MAX(EMPNO) ---------- ---------10 99 SQL> SQL> @select_deptno_literal_10 SQL> set echo on SQL> SQL> select /*CS*/ count(*), max(empno) from emp where deptno = 10; COUNT(*) MAX(EMPNO) ---------- ---------99900 100000



System altered.

Practice 8-2: Understanding CURSOR_SHARING (continued) @show_latest_cursors set echo on col sql_text format a70 select sql_text,hash_value from v$sql where sql_text like '%select /*CS%';

SQL_TEXT HASH_VALUE --------------------------------------------------------------------- ---------select /*CS*/ count(*), max(empno) from emp where deptno = :"SYS_B_0" 3434097775 SQL> @show_latest_exec_plans SQL> set echo on SQL> SQL> col object_name format a5 SQL> col operation format a16 SQL> col options format a15 SQL> SQL> select address,hash_value,child_number, operation,options,object_name 2 from v$sql_plan 3 where (address,hash_value) in 4 (select address,hash_value 5 from v$sql 6 where sql_text like '%select /*CS%'); ADDRESS OBJEC ---------4C9C53D4 4C9C53D4 4C9C53D4 EMP 4C9C53D4 EMP_I

HASH_VALUE CHILD_NUMBER OPERATION

OPTIONS

---------- ------------ ---------------- --------------- -3434097775 3434097775 3434097775

0 SELECT STATEMENT 0 SORT AGGREGATE 0 TABLE ACCESS BY INDEX ROWID

3434097775

0 INDEX

RANGE SCAN 1

SQL> -------------------------------------------------------------set echo on select /*CS*/ count(*), max(empno) from emp where deptno = 9; -------------------------------------------------------------set echo on



SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3

Practice 8-2: Understanding CURSOR_SHARING (continued) select /*CS*/ count(*), max(empno) from emp where deptno = 10; -------------------------------------------------------------set echo on col sql_text format a70 select sql_text,hash_value from v$sql where sql_text like '%select /*CS%';

set echo on col object_name format a5 col operation format a16 col options format a15 select address,hash_value,child_number, operation,options,object_name from v$sql_plan where (address,hash_value) in (select address,hash_value from v$sql where sql_text like '%select /*CS%');

7) Ensure that you create a 10 buckets histogram on the DEPTNO column of the EMP table. SQL> exec dbms_stats.gather_table_stats(null, 'EMP', METHOD_OPT => 'FOR COLUMNS DEPTNO SIZE 10', CASCADE => TRUE); PL/SQL procedure successfully completed. SQL> SQL> SQL> SQL> 2 3



HISTOGRAM NUM_BUCKETS --------------- ----------NONE 1 NONE 1 NONE 1 HEIGHT BALANCED 10

SQL> -------------------------------------------------------------set echo on



--------------------------------------------------------------

Practice 8-2: Understanding CURSOR_SHARING (continued) select column_name, histogram, num_buckets from user_tab_columns where table_name='EMP';

8) Before you continue, ensure that you flush your shared pool. SQL> alter system flush shared_pool; System altered.

9) Perform step 6 again. What do you observe and why? a) Although you captured histogram for the DEPTNO column that shows data skew, the system continues to share only one child cursor to handle both statements. This behavior is due to the FORCE option for the CURSOR_SHARING initialization parameter. SQL> @select_deptno_literal_9 SQL> set echo on SQL> SQL> select /*CS*/ count(*), max(empno) from emp where deptno = 9; COUNT(*) MAX(EMPNO) ---------- ---------10 99 SQL> SQL> @select_deptno_literal_10 SQL> set echo on SQL> SQL> select /*CS*/ count(*), max(empno) from emp where deptno = 10; COUNT(*) MAX(EMPNO) ---------- ---------99900 100000 SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3

@show_latest_cursors set echo on col sql_text format a70 select sql_text,hash_value from v$sql where sql_text like '%select /*CS%';

SQL_TEXT HASH_VALUE --------------------------------------------------------------------- ----------



SQL>

Practice 8-2: Understanding CURSOR_SHARING (continued) select /*CS*/ count(*), max(empno) from emp where deptno = :"SYS_B_0" 3434097775 SQL> -------------------------------------------------------------set echo on select /*CS*/ count(*), max(empno) from emp where deptno = 9; --------------------------------------------------------------

select /*CS*/ count(*), max(empno) from emp where deptno = 10; -------------------------------------------------------------set echo on col sql_text format a70 select sql_text,hash_value from v$sql where sql_text like '%select /*CS%';

10) Before you continue, ensure that you flush your shared pool. SQL> alter system flush shared_pool; System altered. SQL>

11) How would you ensure that you now use more than one child cursor to handle both statements? Implement your solution, and check it. a) By setting CURSOR_SHARING to SIMILAR for your session, the system is able to see that you benefit from using two different child cursors to handle both statements because they lend themselves to very different execution plans. SQL> alter session set cursor_sharing = similar; Session altered. SQL> @select_deptno_literal_9 SQL> set echo on SQL> SQL> select /*CS*/ count(*), max(empno) from emp where deptno = 9; COUNT(*) MAX(EMPNO) ---------- ---------10 99



set echo on

Practice 8-2: Understanding CURSOR_SHARING (continued) SQL> SQL> @select_deptno_literal_10 SQL> set echo on SQL> SQL> select /*CS*/ count(*), max(empno) from emp where deptno = 10; COUNT(*) MAX(EMPNO) ---------- ---------99900 100000

@show_latest_cursors set echo on col sql_text format a70 select sql_text,hash_value from v$sql where sql_text like '%select /*CS%';

SQL_TEXT HASH_VALUE --------------------------------------------------------------------- ---------select /*CS*/ count(*), max(empno) from emp where deptno = :"SYS_B_0" 3434097775 select /*CS*/ count(*), max(empno) from emp where deptno = :"SYS_B_0" 3434097775 SQL> @show_latest_exec_plans SQL> set echo on SQL> SQL> col object_name format a5 SQL> col operation format a16 SQL> col options format a15 SQL> SQL> select address,hash_value,child_number, operation,options,object_name 2 from v$sql_plan 3 where (address,hash_value) in 4 (select address,hash_value 5 from v$sql 6 where sql_text like '%select /*CS%'); ADDRESS OBJEC ---------4C9C53D4 4C9C53D4 4C9C53D4 EMP 4C9C53D4 4C9C53D4 4C9C53D4 EMP

HASH_VALUE CHILD_NUMBER OPERATION

OPTIONS

---------- ------------ ---------------- --------------- -3434097775 3434097775 3434097775

1 SELECT STATEMENT 1 SORT AGGREGATE 1 TABLE ACCESS FULL

3434097775 3434097775 3434097775

0 SELECT STATEMENT 0 SORT AGGREGATE 0 TABLE ACCESS BY INDEX ROWID



SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3

Practice 8-2: Understanding CURSOR_SHARING (continued) 4C9C53D4 3434097775 EMP_I

0 INDEX

RANGE SCAN 1

7 rows selected. SQL> -------------------------------------------------------------set echo on

-------------------------------------------------------------set echo on select /*CS*/ count(*), max(empno) from emp where deptno = 10; -------------------------------------------------------------set echo on col sql_text format a70 select sql_text,hash_value from v$sql where sql_text like '%select /*CS%'; -------------------------------------------------------------set echo on col object_name format a5 col operation format a16 col options format a15 select address,hash_value,child_number, operation,options,object_name from v$sql_plan where (address,hash_value) in (select address,hash_value from v$sql where sql_text like '%select /*CS%');

12) Exit your SQL*Plus session and execute the cs_cleanup.sh script to clean up your environment for this lab. SQL> exit Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Cursor_Sharing]$ [oracle@edrsr33p1-orcl Cursor_Sharing]$ ./cs_cleanup.sh



select /*CS*/ count(*), max(empno) from emp where deptno = 9;

Practice 8-2: Understanding CURSOR_SHARING (continued) SQL*Plus: Release 11.1.0.6.0 - Production on Mon Mar 31 14:15:49 2008 Copyright (c) 1982, 2007, Oracle.



User dropped. SQL> SQL> alter system flush shared_pool; System altered. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Cursor_Sharing]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Cursor_Sharing export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @cs_cleanup.sql -------------------------------------------------------------set echo on drop user cs cascade; alter system flush shared_pool; exit;



SQL> SQL> drop user cs cascade;




Practice 9-1: Using Hints In this practice, you study five different hint cases. They are all independent from each other. Note: You can find all the necessary scripts used for this lab in your $HOME/solutions/Hints directory. You should be using a terminal session connected as the oracle user. 1) From your terminal session, execute the iot_setup.sh script. This script creates an index-organized table. [oracle@edrsr33p1-orcl Hints]$ ./iot_setup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Tue Apr 1 15:17:24 2008 All rights reserved.

Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> drop user iot cascade; drop user iot cascade * ERROR at line 1: ORA-01918: user 'IOT' does not exist

SQL> SQL> create user iot identified by iot default tablespace users temporary tablespace temp; User created. SQL> SQL> grant connect, resource, dba to iot; Grant succeeded. SQL> SQL> connect iot/iot Connected. SQL> SQL> drop table iottab purge; drop table iottab purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> SQL> CREATE TABLE IOTTAB ( 2 OBJECT_ID NUMBER(14, 0) NOT NULL ENABLE 3 , OBJECT_ID_ATT NUMBER(14, 0) NOT NULL ENABLE




Practice 9-1: Using Hints (continued) 4 5 6 7 8 9 10 11 12 13 14 15

, , , , , ,

OBJECT_ID_CAT NUMBER(14, 0) NOT NULL ENABLE BEGIN DATE NOT NULL ENABLE END DATE NOT NULL ENABLE STATUS NUMBER COMM VARCHAR2(32) NOT NULL ENABLE CONSTRAINT IOTTAB_PK PRIMARY KEY (OBJECT_ID , OBJECT_ID_ATT , OBJECT_ID_CAT , BEGIN , END) ENABLE ) ORGANIZATION INDEX PCTTHRESHOLD 50 ;

SQL> SQL> CREATE INDEX OBJECT_ID_ATT_INDX ON IOTTAB (OBJECT_ID_ATT); Index created. SQL> SQL> -- load data SQL> SQL> begin 2 for i in 400001..500000 loop 3 insert into iottab values(i,mod(i,428),mod(i,20),sysdatemod(i,100),sysdate+mod(i,100),mod(i,3),'aaaaaaaaaaaaaaaaaaaaaaaaaa'| |i); 4 end loop; 5 commit; 6 end; 7 / PL/SQL procedure successfully completed. SQL> SQL> SQL> begin 2 for i in 100001..200000 loop 3 insert into iottab values(i,mod(i,428),mod(i,20),sysdatemod(i,100),sysdate+mod(i,100),mod(i,3),'aaaaaaaaaaaaaaaaaaaaaaaaaa'| |i); 4 end loop; 5 commit; 6 end; 7 / PL/SQL procedure successfully completed. SQL> SQL> SQL> begin 2 for i in 300001..400000 loop 3 insert into iottab values(i,mod(i,428),mod(i,20),sysdatemod(i,100),sysdate+mod(i,100),mod(i,3),'aaaaaaaaaaaaaaaaaaaaaaaaaa'| |i); 4 end loop;



Table created.

Practice 9-1: Using Hints (continued) 5 6 7

commit; end; /

SQL> SQL> SQL> begin 2 for i in 500001..600000 loop 3 insert into iottab values(i,mod(i,428),mod(i,20),sysdatemod(i,100),sysdate+mod(i,100),mod(i,3),'aaaaaaaaaaaaaaaaaaaaaaaaaa'| |i); 4 end loop; 5 commit; 6 end; 7 / PL/SQL procedure successfully completed. SQL> SQL> SQL> begin 2 for i in 1..100000 loop 3 insert into iottab values(i,mod(i,428),mod(i,20),sysdatemod(i,100),sysdate+mod(i,100),mod(i,3),'aaaaaaaaaaaaaaaaaaaaaaaaaa'| |i); 4 end loop; 5 commit; 6 end; 7 / PL/SQL procedure successfully completed. SQL> SQL> SQL> SQL> alter system flush shared_pool; System altered. SQL> SQL> alter system flush buffer_cache; System altered. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Hints]$ -------------------------------------------------------------#!/bin/bash




Practice 9-1: Using Hints (continued) cd /home/oracle/solutions/Hints export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @iot_setup.sql

set echo on drop user iot cascade; create user iot identified by iot default tablespace users temporary tablespace temp; grant connect, resource, dba to iot; connect iot/iot drop table iottab purge; CREATE TABLE IOTTAB ( OBJECT_ID NUMBER(14, 0) NOT NULL ENABLE , OBJECT_ID_ATT NUMBER(14, 0) NOT NULL ENABLE , OBJECT_ID_CAT NUMBER(14, 0) NOT NULL ENABLE , BEGIN DATE NOT NULL ENABLE , END DATE NOT NULL ENABLE , STATUS NUMBER , COMM VARCHAR2(32) NOT NULL ENABLE , CONSTRAINT IOTTAB_PK PRIMARY KEY (OBJECT_ID , OBJECT_ID_ATT , OBJECT_ID_CAT , BEGIN , END) ENABLE ) ORGANIZATION INDEX PCTTHRESHOLD 50 ; CREATE INDEX OBJECT_ID_ATT_INDX ON IOTTAB (OBJECT_ID_ATT); -- load data begin for i in 400001..500000 loop insert into iottab values(i,mod(i,428),mod(i,20),sysdatemod(i,100),sysdate+mod(i,100),mod(i,3),'aaaaaaaaaaaaaaaaaaaaaaaaaa'| |i); end loop; commit; end; /



--------------------------------------------------------------

Practice 9-1: Using Hints (continued)

begin for i in 300001..400000 loop insert into iottab values(i,mod(i,428),mod(i,20),sysdatemod(i,100),sysdate+mod(i,100),mod(i,3),'aaaaaaaaaaaaaaaaaaaaaaaaaa'| |i); end loop; commit; end; /



alter system flush shared_pool; alter system flush buffer_cache; exit;




Practice 9-1: Using Hints (continued) 2) From your terminal session, connect as the IOT user in the SQL*Plus session. From your SQL*Plus session, execute the set_session.sql script. This script sets a number of parameters for the duration of this case. Ensure that you do not exit from your SQL*Plus session until asked to do so. [oracle@edrsr33p1-orcl Hints]$ sqlplus iot/iot SQL*Plus: Release 11.1.0.6.0 - Production on Tue Apr 1 15:18:22 2008 All rights reserved.

Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> @set_session Session altered. SQL> -------------------------------------------------------------ALTER SESSION SET OPTIMIZER_INDEX_CACHING=2; set timing on set linesize 200 pagesize 1000

3) From your SQL*Plus session, execute the following query and note down the time it takes to execute: SELECT FROM WHERE AND AND

comm. iottab object_id = 1 object_id_cat = 0 object_id_att = 426 ;

SQL> @select_iot SQL> SQL> SELECT comm 2 FROM iottab 3 WHERE object_id = 1 4 AND object_id_cat = 0 5 AND object_id_att = 426 ; no rows selected Elapsed: 00:00:00.07 SQL> -------------------------------------------------------------set echo on




Practice 9-1: Using Hints (continued) SELECT FROM WHERE AND AND

comm iottab object_id = 1 object_id_cat = 0 object_id_att = 426 ;

4) Use the DBMS_XPLAN package to display the execution plan associated with the statement you executed in the previous step. What do you observe?

SQL> @show_latest_exec_plan SQL> set echo on SQL> SQL> select * from table(dbms_xplan.display_cursor(null,null,'TYPICAL')); PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID 6u4tsfpprgvzn, child number 0 ------------------------------------SELECT comm FROM iottab WHERE object_id = 1 AND object_id_cat = 0 AND object_id_att = 426 Plan hash value: 2544181447 --------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | | | 1 (100)| | |* 1 | INDEX UNIQUE SCAN| IOTTAB_PK | 1 | 57 | 1 (0)| 00:00:01 | |* 2 | INDEX RANGE SCAN| OBJECT_ID_ATT_INDX | 50 | | 1 (0)| 00:00:01 | --------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 - access("OBJECT_ID_ATT"=426) filter(("OBJECT_ID"=1 AND "OBJECT_ID_CAT"=0)) 2 - access("OBJECT_ID_ATT"=426) Note ----- dynamic sampling used for this statement



a) It is strange to see that the optimizer chooses a plan that accesses the secondary index while the query references all columns of the primary key.

Practice 9-1: Using Hints (continued) 26 rows selected. Elapsed: 00:00:00.13 SQL> -------------------------------------------------------------set echo on

5) Before trying to fix this issue, make sure you flush the important content of your SGA by executing the flush_sga.sql script. SQL> @flush_sga SQL> set echo on SQL> SQL> alter system flush shared_pool; System altered. Elapsed: 00:00:00.11 SQL> SQL> alter system flush buffer_cache; System altered. Elapsed: 00:00:00.43 SQL> -------------------------------------------------------------set echo on alter system flush shared_pool; alter system flush buffer_cache;

6) Using hints only, how would you fix the issue raised at step 4? Implement your solution and check if it works. a) The idea is to use a hint to prevent the optimizer from using the secondary index. You will not use the NO_INDEX hint. SQL> @select_iot_hint SQL> set echo on SQL> SQL> SELECT /*+ NO_INDEX(t OBJECT_ID_ATT_INDX) */ comm 2 FROM iottab t 3 WHERE object_id = 1 4 AND object_id_cat = 0 5 AND object_id_att = 426 ;



select * from table(dbms_xplan.display_cursor(null,null,'TYPICAL'));

Practice 9-1: Using Hints (continued) no rows selected

PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID 4zcxy7z1cg8da, child number 0 ------------------------------------SELECT /*+ NO_INDEX(t OBJECT_ID_ATT_INDX) */ comm FROM iottab t WHERE object_id = 1 AND object_id_cat = 0 AND object_id_att = 426 Plan hash value: 181430399 ----------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ----------------------------------------------------------------------------| 0 | SELECT STATEMENT | | | | 1 (100)| | |* 1 | INDEX RANGE SCAN| IOTTAB_PK | 1 | 57 | 1 (0)| 00:00:01 | ----------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 - access("OBJECT_ID"=1 AND "OBJECT_ID_ATT"=426 AND "OBJECT_ID_CAT"=0) Note ----- dynamic sampling used for this statement

24 rows selected. Elapsed: 00:00:00.13 SQL> -------------------------------------------------------------set echo on SELECT /*+ NO_INDEX(t OBJECT_ID_ATT_INDX) */ comm FROM iottab t



Elapsed: 00:00:00.03 SQL> SQL> @show_latest_exec_plan SQL> set echo on SQL> SQL> select * from table(dbms_xplan.display_cursor(null,null,'TYPICAL'));

Practice 9-1: Using Hints (continued) WHERE object_id = 1 AND object_id_cat = 0 AND object_id_att = 426 ; -------------------------------------------------------------set echo on select * from table(dbms_xplan.display_cursor(null,null,'TYPICAL'));

SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Hints]$ [oracle@edrsr33p1-orcl Hints]$ ./iot_cleanup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Tue Apr 1 15:21:09 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> drop user iot cascade; User dropped. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Hints]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Hints export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1



7) Exit from your SQL*Plus session, and clean up your environment by executing the iot_cleanup.sh script.

Practice 9-1: Using Hints (continued) export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @iot_cleanup.sql -------------------------------------------------------------set echo on drop user iot cascade;

8) You study a second case of hint utilization to specify hints in lower query blocks. From your terminal session connected as the oracle user, execute the hr_hint_setup.sh script. [oracle@edrsr33p1-orcl Hints]$ ./hr_hint_setup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Tue Apr 1 16:08:51 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> alter user hr identified by hr account unlock; User altered. SQL> SQL> grant dba to hr 2 SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Hints]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Hints export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1



exit;

Practice 9-1: Using Hints (continued) export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @hr_hint_setup.sql -------------------------------------------------------------set echo on alter user hr identified by hr account unlock; grant dba to hr

9) From your terminal session, connect as the HR user in the SQL*Plus session. After you are connected, execute the create_hr_view1.sql script that creates a view called V1 on top of the EMPLOYEES table. After this is done, execute the create_hr_view2.sql script that creates a view V2 on top of V1. [oracle@edrsr33p1-orcl Hints]$ sqlplus hr/hr SQL*Plus: Release 11.1.0.6.0 - Production on Tue Apr 1 16:09:02 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> @create_hr_view1 SQL> SQL> CREATE OR REPLACE VIEW v1 AS 2 SELECT * 3 FROM employees 4 WHERE employee_id < 150; View created. SQL> SQL> @create_hr_view2 SQL> set echo on SQL> SQL> CREATE OR REPLACE VIEW v2 AS 2 SELECT v1.employee_id employee_id, departments.department_id department_id 3 FROM v1, departments 4 WHERE v1.department_id = departments.department_id; View created.



exit;

Practice 9-1: Using Hints (continued) SQL> -------------------------------------------------------------set echo on CREATE OR REPLACE VIEW v1 AS SELECT * FROM employees WHERE employee_id < 150; --------------------------------------------------------------

CREATE OR REPLACE VIEW v2 AS SELECT v1.employee_id employee_id, departments.department_id department_id FROM v1, departments WHERE v1.department_id = departments.department_id;

10) Determine the execution plan used to process the following query: SELECT * FROM v2 WHERE department_id = 30; SQL> SQL> SQL> SQL> SQL> 2 3 4

set linesize 200 pagesize 1000 @show_exec_plan_view2 set echo on explain plan for SELECT * FROM v2 WHERE department_id = 30;

Explained. SQL> SQL> select * from table(DBMS_XPLAN.DISPLAY(null,null,'ALL')); PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Plan hash value: 389887213 ------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 3 | 33 | 1 (0)| 00:00:01 | | 1 | NESTED LOOPS | | 3 | 33 | 1 (0)| 00:00:01 | |* 2 | INDEX UNIQUE SCAN | DEPT_ID_PK | 1 | 4 | 0 (0)| 00:00:01 |



set echo on

Practice 9-1: Using Hints (continued) |* 3 | TABLE ACCESS BY INDEX ROWID| EMPLOYEES | 3 | 21 | 1 (0)| 00:00:01 | |* 4 | INDEX RANGE SCAN | EMP_DEPARTMENT_IX | 6 | | 0 (0)| 00:00:01 | ------------------------------------------------------------------------------------------------Query Block Name / Object Alias (identified by operation id): -------------------------------------------------------------

SEL$5C160134 SEL$5C160134 / DEPARTMENTS@SEL$2 SEL$5C160134 / EMPLOYEES@SEL$3 SEL$5C160134 / EMPLOYEES@SEL$3

Predicate Information (identified by operation id): --------------------------------------------------2 - access("DEPARTMENTS"."DEPARTMENT_ID"=30) 3 - filter("EMPLOYEE_ID"<150) 4 - access("DEPARTMENT_ID"=30) Column Projection Information (identified by operation id): ----------------------------------------------------------1 - (#keys=0) "DEPARTMENTS"."DEPARTMENT_ID"[NUMBER,22], "EMPLOYEE_ID"[NUMBER,22] 2 - "DEPARTMENTS"."DEPARTMENT_ID"[NUMBER,22] 3 - "EMPLOYEE_ID"[NUMBER,22] 4 - "EMPLOYEES".ROWID[ROWID,10] 34 rows selected. SQL> -------------------------------------------------------------set echo on explain plan for SELECT * FROM v2 WHERE department_id = 30; select * from table(DBMS_XPLAN.DISPLAY(null,null,'ALL'));

11) How do you force the query from step 10 to do a full table scan of the departments table and a range scan of the emp_emp_id_pk index? a) You have to use extended hint syntax to be able to specify hints that apply to tables and indexes that appear in views. The NO_MERGE hint is used to make sure that the view is not merged into the surrounding query blocks. SQL> @show_exec_plan_view2_hints SQL> set echo on SQL>



1 2 3 4

Practice 9-1: Using Hints (continued) SQL> explain plan for 2 SELECT /*+ NO_MERGE(v2) INDEX(v2.v1.employees emp_emp_id_pk) FULL(v2.departments) */ * 3 FROM v2 4 WHERE department_id = 30; Explained.

PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Plan hash value: 1511767168 ---------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ---------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 3 | 78 | 5 (0)| 00:00:01 | | 1 | VIEW | V2 | 3 | 78 | 5 (0)| 00:00:01 | | 2 | NESTED LOOPS | | | | | | | 3 | NESTED LOOPS | | 3 | 57 | 5 (0)| 00:00:01 | |* 4 | TABLE ACCESS FULL | DEPARTMENTS | 1 | 8 | 3 (0)| 00:00:01 | |* 5 | INDEX RANGE SCAN | EMP_EMP_ID_PK | 50 | | 1 (0)| 00:00:01 | |* 6 | TABLE ACCESS BY INDEX ROWID| EMPLOYEES | 3 | 33 | 2 (0)| 00:00:01 | ---------------------------------------------------------------------------------------------Query Block Name / Object Alias (identified by operation id): ------------------------------------------------------------1 2 4 5 6

-

SEL$335DD26A SEL$335DD26A SEL$335DD26A SEL$335DD26A SEL$335DD26A

/ V2@SEL$1 / DEPARTMENTS@SEL$2 / EMPLOYEES@SEL$3 / EMPLOYEES@SEL$3

Predicate Information (identified by operation id): --------------------------------------------------4 - filter("DEPARTMENTS"."DEPARTMENT_ID"=30) 5 - access("EMPLOYEE_ID"<150) 6 - filter("DEPARTMENT_ID"=30) Column Projection Information (identified by operation id):



SQL> SQL> select * from table(DBMS_XPLAN.DISPLAY(null,null,'ALL'));

Practice 9-1: Using Hints (continued) ----------------------------------------------------------1 - "V2"."EMPLOYEE_ID"[NUMBER,22], "V2"."DEPARTMENT_ID"[NUMBER,22] 2 - (#keys=0) "DEPARTMENTS"."DEPARTMENT_ID"[NUMBER,22], "EMPLOYEE_ID"[NUMBER,22] 3 - (#keys=0) "DEPARTMENTS"."DEPARTMENT_ID"[NUMBER,22], "EMPLOYEES".ROWID[ROWID,10], "EMPLOYEE_ID"[NUMBER,22] 4 - "DEPARTMENTS"."DEPARTMENT_ID"[NUMBER,22] 5 - "EMPLOYEES".ROWID[ROWID,10], "EMPLOYEE_ID"[NUMBER,22] 39 rows selected.

-------------------------------------------------------------set echo on explain plan for SELECT /*+ NO_MERGE(v2) INDEX(v2.v1.employees emp_emp_id_pk) FULL(v2.departments) */ * FROM v2 WHERE department_id = 30; select * from table(DBMS_XPLAN.DISPLAY(null,null,'ALL'));

12) Exit from your SQL*Plus session and clean up your environment by executing the hr_hint_cleanup.sh script. SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Hints]$ ./hr_hint_cleanup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Tue Apr 1 16:10:09 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> revoke dba from hr; revoke dba from hr * ERROR at line 1: ORA-01951: ROLE 'DBA' not granted to 'HR'



SQL>

Practice 9-1: Using Hints (continued) SQL> SQL> drop view hr.v1; View dropped. SQL> SQL> drop view hr.v2;

SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Hints]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Hints export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @hr_hint_cleanup.sql -------------------------------------------------------------set echo on revoke dba from hr; drop view hr.v1; drop view hr.v2; exit;

13) In this third case, you investigate how to influence optimizer’s joins. From your terminal session, execute the sh_hint_setup.sh script. [oracle@edrsr33p1-orcl Hints]$ ./sh_hint_setup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Tue Apr 1 19:38:18 2008 Copyright (c) 1982, 2007, Oracle.




View dropped.

Practice 9-1: Using Hints (continued) Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options

SQL> SQL> grant dba to sh; Grant succeeded. SQL> SQL> connect sh/sh Connected. SQL> SQL> exec dbms_stats.delete_schema_stats('SH'); PL/SQL procedure successfully completed. SQL> SQL> exec dbms_stats.set_table_stats('SH','SALES',null,null,null,10,5); PL/SQL procedure successfully completed. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Hints]$ [oracle@edrsr33p1-orcl Hints]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Hints export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @sh_hint_setup.sql



SQL> SQL> alter user sh identified by sh acccount unlock; alter user sh identified by sh acccount unlock * ERROR at line 1: ORA-00922: missing or invalid option

Practice 9-1: Using Hints (continued) -------------------------------------------------------------set echo on alter user sh identified by sh acccount unlock; grant dba to sh; connect sh/sh exec dbms_stats.delete_schema_stats('SH');

exit;

14) From your terminal session, connect as the SH user in the SQL*Plus session. After you are connected, ensure that you flush your SGA content using the flush_sga.sql script, and set some important session parameters using the set_sh_session.sql script. Ensure that you do not disconnect from your established SQL*Plus session. [oracle@edrsr33p1-orcl Hints]$ sqlplus sh/sh SQL*Plus: Release 11.1.0.6.0 - Production on Tue Apr 1 19:38:35 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> @flush_sga SQL> SQL> alter system flush shared_pool; System altered. SQL> SQL> alter system flush buffer_cache; System altered. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL>

@set_sh_session set linesize 200 set pagesize 200 set timing on



exec dbms_stats.set_table_stats('SH','SALES',null,null,null,10,5);

Practice 9-1: Using Hints (continued) SQL> SQL> alter session set optimizer_dynamic_sampling=0; Session altered. Elapsed: 00:00:00.00 SQL> -------------------------------------------------------------set echo on alter system flush shared_pool;

-------------------------------------------------------------set linesize 200 set pagesize 200 set timing on alter session set optimizer_dynamic_sampling=0;

15) From your SQL*Plus session, execute the following query and determine its execution plan: select count(*) from sales s, customers c where s.cust_id=c.cust_id; SQL> @exec_and_show_sh_exec_plan SQL> set echo on SQL> SQL> select count(*) from sales s, customers c where s.cust_id=c.cust_id; COUNT(*) ---------918843 Elapsed: 00:00:03.59 SQL> SQL> select * from table(dbms_xplan.display_cursor(null,null,'TYPICAL')); PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID 88r79fy8nphrc, child number 0 ------------------------------------select count(*) from sales s, customers c where s.cust_id=c.cust_id Plan hash value: 2841872969



alter system flush buffer_cache;

----------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | Pstart| Pstop | ----------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | | | 3 (100)| | | | | 1 | SORT AGGREGATE | | 1 | 26 | | | | | | 2 | NESTED LOOPS | | 121K| 3081K| 3 (0)| 00:00:01 | | | | 3 | PARTITION RANGE ALL| | 10 | 130 | 3 (0)| 00:00:01 | 1 | 28 | | 4 | TABLE ACCESS FULL | SALES | 10 | 130 | 3 (0)| 00:00:01 | 1 | 28 | |* 5 | INDEX UNIQUE SCAN | CUSTOMERS_PK | 12138 | 154K| 0 (0)| | | | ----------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------5 - access("S"."CUST_ID"="C"."CUST_ID")

22 rows selected. Elapsed: 00:00:00.15 SQL> -------------------------------------------------------------set echo on select count(*) from sales s, customers c where s.cust_id=c.cust_id; select * from table(dbms_xplan.display_cursor(null,null,'TYPICAL'));

16) Before you continue, ensure that you flush the content of your SGA to avoid caching issues later. Use the flush_sga.sql script. SQL> @flush_sga SQL> set echo on SQL> SQL> alter system flush shared_pool; System altered. Elapsed: 00:00:00.12 SQL> SQL> alter system flush buffer_cache; System altered.




Practice 9-1: Using Hints (continued) Elapsed: 00:00:00.18 SQL> -------------------------------------------------------------set echo on alter system flush shared_pool; alter system flush buffer_cache;

a) In step 15, the optimizer chose a NESTED LOOPS join. You can try to force a hash join instead, using the LEADING and USE_HASH hints. SQL> @exec_and_show_sh_hint_exec_plan SQL> set echo on SQL> SQL> select /*+ LEADING(c s) USE_HASH(s) */ count(*) from sales s, customers c where s.cust_id=c.cust_id; COUNT(*) ---------918843 Elapsed: 00:00:00.40 SQL> SQL> select * from table(dbms_xplan.display_cursor(null,null,'TYPICAL')); PLAN_TABLE_OUTPUT -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------SQL_ID 9k8wcn7ckb7c1, child number 0 ------------------------------------select /*+ LEADING(c s) USE_HASH(s) */ count(*) from sales s, customers c where s.cust_id=c.cust_id Plan hash value: 3568173901 -------------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time | Pstart| Pstop | -------------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | | | | 182 (100)| | | | | 1 | SORT AGGREGATE | | 1 | 26 | | | | | | |* 2 | HASH JOIN | | 121K| 3081K| 2968K| 182 (2)| 00:00:02 | | |



17) Using hints only, how would you enhance the performance of the same query you executed in step 15? Make sure you verify your implementation.

Practice 9-1: Using Hints (continued) | 3 | INDEX FAST FULL SCAN| CUSTOMERS_PK | 121K| 1540K| | 9 (0)| 00:00:01 | | | | 4 | PARTITION RANGE ALL | | 10 | 130 | | 3 (0)| 00:00:01 | 1 | 28 | | 5 | TABLE ACCESS FULL | SALES | 10 | 130 | | 3 (0)| 00:00:01 | 1 | 28 | -------------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): ---------------------------------------------------

23 rows selected. Elapsed: 00:00:00.13 SQL> -------------------------------------------------------------set echo on select /*+ LEADING(c s) USE_HASH(s) */ count(*) from sales s, customers c where s.cust_id=c.cust_id; select * from table(dbms_xplan.display_cursor(null,null,'TYPICAL'));

18) Exit from your SQL*Plus session and clean up your environment by executing the sh_hint_cleanup.sh script. SQL> exit Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Hints]$ [oracle@edrsr33p1-orcl Hints]$ ./sh_hint_cleanup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Tue Apr 1 19:43:04 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> Connected. SQL> SQL> User altered. SQL> SQL> revoke dba from sh



2 - access("S"."CUST_ID"="C"."CUST_ID")

Practice 9-1: Using Hints (continued) * ERROR at line 1: ORA-01951: ROLE 'DBA' not granted to 'SH'

SQL> SQL> Rem Rem $Header: sh_main.sql 06-mar-2008.15:00:45 cbauwens Exp $ Rem Rem sh_main.sql Rem Rem SET ECHO OFF

specify password for SH as parameter 1: specify default tablespace for SH as parameter 2: specify temporary tablespace for SH as parameter 3: specify password for SYS as parameter 4: specify directory path for the data files as parameter 5: writeable directory path for the log files as parameter 6: specify version as parameter 7:

Session altered.

User dropped. old new

1: CREATE USER sh IDENTIFIED BY &pass 1: CREATE USER sh IDENTIFIED BY sh

User created. old new old new

1: ALTER USER sh DEFAULT TABLESPACE &tbs 1: ALTER USER sh DEFAULT TABLESPACE example 2: QUOTA UNLIMITED ON &tbs 2: QUOTA UNLIMITED ON example

User altered. old new

1: ALTER USER sh TEMPORARY TABLESPACE &ttbs 1: ALTER USER sh TEMPORARY TABLESPACE temp

User altered.

Grant succeeded.

...



SQL> SQL> SQL> SQL> SQL> ... SQL> SQL> SQL>

Practice 9-1: Using Hints (continued) Grant succeeded.

PL/SQL procedure successfully completed. Connected. Grant succeeded.

Directory created. old new

1: CREATE OR REPLACE DIRECTORY log_file_dir AS '&log_dir' 1: CREATE OR REPLACE DIRECTORY log_file_dir AS '/home/oracle/'

Directory created.

Grant succeeded.

Grant succeeded.

Grant succeeded. Connected. Session altered.

Session altered.

Table created.

...

Comment created.

Creating OLAP metadata ... <<<<< CREATE CWMLite Metadata for the Sales History Schema >>>>> … <<<<< FINAL PROCESSING >>>>> - Changes have been committed PL/SQL procedure successfully completed.



old 1: CREATE OR REPLACE DIRECTORY data_file_dir AS '&data_dir' new 1: CREATE OR REPLACE DIRECTORY data_file_dir AS '/u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/'

Practice 9-1: Using Hints (continued) Commit complete.


SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Hints]$

19) With this fourth case, you study the influence of the INDEX and AND_EQUAL hints. From your terminal session, execute the sh_hint_index_setup.sh script to set up the environment for this lab. [oracle@edrsr33p1-orcl Hints]$ ./sh_hint_index_setup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Tue Apr 1 20:16:22 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> alter user sh identified by sh acccount unlock; alter user sh identified by sh acccount unlock * ERROR at line 1: ORA-00922: missing or invalid option

SQL> SQL> grant dba to sh; Grant succeeded. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Hints]$ --------------------------------------------------------------




Practice 9-1: Using Hints (continued) #!/bin/bash cd /home/oracle/solutions/Hints export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin

-------------------------------------------------------------set echo on alter user sh identified by sh acccount unlock; grant dba to sh; exit;

20) From your terminal session, connect to the SQL*Plus session as the SH user. After you are connected, execute the following scripts to further set up your environment for this lab. Ensure that you stay connected to your session throughout this case. [oracle@edrsr33p1-orcl Hints]$ sqlplus sh/sh SQL*Plus: Release 11.1.0.6.0 - Production on Tue Apr 1 20:16:28 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> @drop_index_customers SQL> SQL> @dait SQL> SQL> drop index CUSTOMERS_YOB_BIX; Index dropped. SQL> drop index CUSTOMERS_MARITAL_BIX; Index dropped. SQL> drop index CUSTOMERS_GENDER_BIX;



sqlplus / as sysdba @sh_hint_index_setup.sql

Practice 9-1: Using Hints (continued) Index dropped. SQL> SQL> SQL> SQL> SQL> SQL> 2 3

@create_cust_indexes set echo on CREATE INDEX CUST_CUST_GENDER_idx ON CUSTOMERS(CUST_GENDER) NOLOGGING COMPUTE STATISTICS;

SQL> SQL> CREATE INDEX CUST_CUST_POSTAL_CODE_idx 2 ON CUSTOMERS(CUST_POSTAL_CODE) 3 NOLOGGING COMPUTE STATISTICS; Index created. SQL> SQL> CREATE INDEX CUST_CUST_CREDIT_LIMIT_idx 2 ON CUSTOMERS(CUST_CREDIT_LIMIT) 3 NOLOGGING COMPUTE STATISTICS; Index created. SQL> -------------------------------------------------------------REM REM REM

drop all indexes on CUSTOMERS table does not touch indexes associated with constraints ==================================================

set store save set

termout off set sqlplus_settings replace buffer.sql replace heading off verify off autotrace off feedback off

spool

dait.sql

SELECT 'drop index '||i.index_name||';' FROM user_indexes i WHERE i.table_name = 'CUSTOMERS' AND NOT EXISTS (SELECT 'x' FROM user_constraints c WHERE c.index_name = i.index_name AND c.table_name = i.table_name AND c.status = 'ENABLED'); spool

off

get buffer.sql nolist @sqlplus_settings set termout on



Index created.

Practice 9-1: Using Hints (continued) set echo on @dait -------------------------------------------------------------set echo on

CREATE INDEX CUST_CUST_POSTAL_CODE_idx ON CUSTOMERS(CUST_POSTAL_CODE) NOLOGGING COMPUTE STATISTICS; CREATE INDEX CUST_CUST_CREDIT_LIMIT_idx ON CUSTOMERS(CUST_CREDIT_LIMIT) NOLOGGING COMPUTE STATISTICS;

21) Determine the execution plan for the following query: SELECT c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 AND cust_credit_limit = 10000; SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5 6 7

set autotrace traceonly set linesize 200 pagesize 1000 @index set echo on SELECT c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 AND cust_credit_limit = 10000 /

6 rows selected.

Execution Plan ---------------------------------------------------------Plan hash value: 2008213504 -----------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------



CREATE INDEX CUST_CUST_GENDER_idx ON CUSTOMERS(CUST_GENDER) NOLOGGING COMPUTE STATISTICS;

Practice 9-1: Using Hints (continued) | 0 | SELECT STATEMENT | | 6 | 1080 | 448 (1)| 00:00:05 | |* 1 | TABLE ACCESS FULL| CUSTOMERS | 6 | 1080 | 448 (1)| 00:00:05 | -----------------------------------------------------------------------------Predicate Information (identified by operation id): ---------------------------------------------------

Statistics ---------------------------------------------------------1 recursive calls 0 db block gets 1460 consistent gets 0 physical reads 0 redo size 2570 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 6 rows processed SQL> -------------------------------------------------------------set echo on SELECT c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 AND cust_credit_limit = 10000 /

22) Try to get a better execution plan using the INDEX hint for the same query you investigated in step 21. Which index is best suited? a) The CUST_CUST_GENDER_IDX index is the best one for this query. Note that using the INDEX hint without specifying any index leads the optimizer to use the CUST_CUST_GENDER_IDX index. SQL> SQL> SQL> SQL> 2 3 4

@index_hint set echo on SELECT /*+ INDEX (c &indexname) */ c.* FROM customers c WHERE cust_gender = 'M'



1 - filter(TO_NUMBER("CUST_POSTAL_CODE")=40804 AND "CUST_CREDIT_LIMIT"=10000 AND "CUST_GENDER"='M')

Practice 9-1: Using Hints (continued) 5 AND cust_postal_code = 40804 6 AND cust_credit_limit = 10000 7 / Enter value for indexname: CUST_CUST_CREDIT_LIMIT_IDX old 1: SELECT /*+ INDEX (c &indexname) */ new 1: SELECT /*+ INDEX (c CUST_CUST_CREDIT_LIMIT_IDX) */ 6 rows selected.

--------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 6 | 1080 | 1074 (1)| 00:00:11 | |* 1 | TABLE ACCESS BY INDEX ROWID| CUSTOMERS | 6 | 1080 | 1074 (1)| 00:00:11 | |* 2 | INDEX RANGE SCAN | CUST_CUST_CREDIT_LIMIT_IDX | 6938 | | 14 (0)| 00:00:01 | --------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 - filter(TO_NUMBER("CUST_POSTAL_CODE")=40804 AND "CUST_GENDER"='M') 2 - access("CUST_CREDIT_LIMIT"=10000)

Statistics ---------------------------------------------------------1 recursive calls 0 db block gets 1053 consistent gets 13 physical reads 0 redo size 2570 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 6 rows processed SQL> SQL> SQL> SQL> SQL> 2

@index_hint set echo on SELECT /*+ INDEX (c &indexname) */ c.*




Practice 9-1: Using Hints (continued) 3 FROM customers c 4 WHERE cust_gender = 'M' 5 AND cust_postal_code = 40804 6 AND cust_credit_limit = 10000 7 / Enter value for indexname: CUST_CUST_GENDER_IDX old 1: SELECT /*+ INDEX (c &indexname) */ new 1: SELECT /*+ INDEX (c CUST_CUST_GENDER_IDX) */ 6 rows selected.

--------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 6 | 1080 | 1164 (1)| 00:00:12 | |* 1 | TABLE ACCESS BY INDEX ROWID| CUSTOMERS | 6 | 1080 | 1164 (1)| 00:00:12 | |* 2 | INDEX RANGE SCAN | CUST_CUST_GENDER_IDX | 27750 | | 51 (0)| 00:00:01 | --------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 - filter(TO_NUMBER("CUST_POSTAL_CODE")=40804 AND "CUST_CREDIT_LIMIT"=10000) 2 - access("CUST_GENDER"='M')

Statistics ---------------------------------------------------------1 recursive calls 0 db block gets 1399 consistent gets 68 physical reads 0 redo size 2570 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 6 rows processed SQL> SQL> @index_hint SQL> set echo on SQL>




Practice 9-1: Using Hints (continued) SQL> SELECT /*+ INDEX (c &indexname) */ 2 c.* 3 FROM customers c 4 WHERE cust_gender = 'M' 5 AND cust_postal_code = 40804 6 AND cust_credit_limit = 10000 7 / Enter value for indexname: CUST_CUST_POSTAL_CODE_IDX old 1: SELECT /*+ INDEX (c &indexname) */ new 1: SELECT /*+ INDEX (c CUST_CUST_POSTAL_CODE_IDX) */

Execution Plan ---------------------------------------------------------Plan hash value: 1928091631 -------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 6 | 1080 | 218 (1)| 00:00:03 | |* 1 | TABLE ACCESS BY INDEX ROWID| CUSTOMERS | 6 | 1080 | 218 (1)| 00:00:03 | |* 2 | INDEX FULL SCAN | CUST_CUST_POSTAL_CODE_IDX | 89 | | 134 (1)| 00:00:02 | -------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 - filter("CUST_CREDIT_LIMIT"=10000 AND "CUST_GENDER"='M') 2 - filter(TO_NUMBER("CUST_POSTAL_CODE")=40804)

Statistics ---------------------------------------------------------1 recursive calls 0 db block gets 251 consistent gets 132 physical reads 0 redo size 2570 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 6 rows processed SQL> SQL> @index_hint SQL> set echo on



6 rows selected.

Practice 9-1: Using Hints (continued) SQL> SQL> SELECT /*+ INDEX (c &indexname) */ 2 c.* 3 FROM customers c 4 WHERE cust_gender = 'M' 5 AND cust_postal_code = 40804 6 AND cust_credit_limit = 10000 7 / Enter value for indexname: old 1: SELECT /*+ INDEX (c &indexname) */ new 1: SELECT /*+ INDEX (c ) */

Execution Plan ---------------------------------------------------------Plan hash value: 1928091631 -------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 6 | 1080 | 218 (1)| 00:00:03 | |* 1 | TABLE ACCESS BY INDEX ROWID| CUSTOMERS | 6 | 1080 | 218 (1)| 00:00:03 | |* 2 | INDEX FULL SCAN | CUST_CUST_POSTAL_CODE_IDX | 89 | | 134 (1)| 00:00:02 | -------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 - filter("CUST_CREDIT_LIMIT"=10000 AND "CUST_GENDER"='M') 2 - filter(TO_NUMBER("CUST_POSTAL_CODE")=40804)




6 rows selected.

Practice 9-1: Using Hints (continued) -------------------------------------------------------------set echo on SELECT /*+ INDEX (c &indexname) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 AND cust_credit_limit = 10000 /

a) Using the AND_EQUAL hint allows the optimizer to explicitly choose an execution plan that uses an access path that merges the scans on several singlecolumn indexes. However, no combination is better than the CUST_CUST_GENDER_IDX index. SQL> @and_equal_hint SQL> set echo on SQL> SQL> SELECT /*+ AND_EQUAL (c &index_name1, &index_name2) */ 2 c.* 3 FROM customers c 4 WHERE cust_gender = 'M' 5 AND cust_postal_code = 40804 6 AND cust_credit_limit = 10000 7 / Enter value for index_name1: CUST_CUST_CREDIT_LIMIT_IDX Enter value for index_name2: CUST_CUST_GENDER_IDX old 1: SELECT /*+ AND_EQUAL (c &index_name1, &index_name2) */ new 1: SELECT /*+ AND_EQUAL (c CUST_CUST_CREDIT_LIMIT_IDX, CUST_CUST_GENDER_IDX) */ 6 rows selected.

Execution Plan ---------------------------------------------------------Plan hash value: 1121089724 --------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | --------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 6 | 1080 | 1416 (1)| 00:00:15 | |* 1 | TABLE ACCESS BY INDEX ROWID| CUSTOMERS | 6 | 1080 | 1416 (1)| 00:00:15 | | 2 | AND-EQUAL | | | | | |



23) Investigate the same query, but this time using the AND_EQUAL hint. Can you find a better execution plan with this hint?

Practice 9-1: Using Hints (continued) |* 3 | INDEX RANGE SCAN | CUST_CUST_CREDIT_LIMIT_IDX | 6938 | | 14 (0)| 00:00:01 | |* 4 | INDEX RANGE SCAN | CUST_CUST_GENDER_IDX | 27750 | | 51 (0)| 00:00:01 | --------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): ---------------------------------------------------

Statistics ---------------------------------------------------------1 recursive calls 0 db block gets 9160 consistent gets 0 physical reads 0 redo size 2570 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 6 rows processed SQL> SQL> @and_equal_hint SQL> set echo on SQL> SQL> SELECT /*+ AND_EQUAL (c &index_name1, &index_name2) */ 2 c.* 3 FROM customers c 4 WHERE cust_gender = 'M' 5 AND cust_postal_code = 40804 6 AND cust_credit_limit = 10000 7 / Enter value for index_name1: CUST_CUST_CREDIT_LIMIT_IDX Enter value for index_name2: CUST_CUST_POSTAL_CODE_IDX old 1: SELECT /*+ AND_EQUAL (c &index_name1, &index_name2) */ new 1: SELECT /*+ AND_EQUAL (c CUST_CUST_CREDIT_LIMIT_IDX, CUST_CUST_POSTAL_CODE_IDX) */ 6 rows selected.

Execution Plan ---------------------------------------------------------Plan hash value: 1928091631 --------------------------------------------------------------------------------------------------------



1 - filter(TO_NUMBER("CUST_POSTAL_CODE")=40804 AND "CUST_CREDIT_LIMIT"=10000 AND "CUST_GENDER"='M') 3 - access("CUST_CREDIT_LIMIT"=10000) 4 - access("CUST_GENDER"='M')

Practice 9-1: Using Hints (continued) | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 6 | 1080 | 218 (1)| 00:00:03 | |* 1 | TABLE ACCESS BY INDEX ROWID| CUSTOMERS | 6 | 1080 | 218 (1)| 00:00:03 | |* 2 | INDEX FULL SCAN | CUST_CUST_POSTAL_CODE_IDX | 89 | | 134 (1)| 00:00:02 | --------------------------------------------------------------------------------------------------------

1 - filter("CUST_CREDIT_LIMIT"=10000 AND "CUST_GENDER"='M') 2 - filter(TO_NUMBER("CUST_POSTAL_CODE")=40804)

Statistics ---------------------------------------------------------1 recursive calls 0 db block gets 251 consistent gets 0 physical reads 0 redo size 2570 bytes sent via SQL*Net to client 420 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 6 rows processed SQL> -------------------------------------------------------------set echo on SELECT /*+ AND_EQUAL (c &index_name1, &index_name2) */ c.* FROM customers c WHERE cust_gender = 'M' AND cust_postal_code = 40804 AND cust_credit_limit = 10000 /

24) Exit from your SQL*Plus session and clean up your environment by executing the sh_hint_cleanup.sh script. SQL> exit Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options




Practice 9-1: Using Hints (continued) [oracle@edrsr33p1-orcl Hints]$ [oracle@edrsr33p1-orcl Hints]$ ./sh_hint_cleanup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Tue Apr 1 19:43:04 2008 Copyright (c) 1982, 2007, Oracle.


SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> Connected. SQL> SQL> User altered. SQL> SQL> revoke dba from sh * ERROR at line 1: ORA-01951: ROLE 'DBA' not granted to 'SH'

SQL> SQL> SQL> SQL> SQL> ... SQL> SQL> SQL>

SQL> SQL> Rem Rem $Header: sh_main.sql 06-mar-2008.15:00:45 cbauwens Exp $ Rem Rem sh_main.sql Rem Rem SET ECHO OFF


Session altered.






Practice 9-1: Using Hints (continued) User created. old new old new




Grant succeeded.

...

Grant succeeded.

PL/SQL procedure successfully completed. Connected. Grant succeeded. old 1: CREATE OR REPLACE DIRECTORY data_file_dir AS '&data_dir' new 1: CREATE OR REPLACE DIRECTORY data_file_dir AS '/u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/' Directory created. old new


Directory created.

Grant succeeded.

Grant succeeded.


Session altered.



User altered.

Practice 9-1: Using Hints (continued) Table created.

...

Comment created.


Commit complete.


PL/SQL procedure successfully completed. SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Hints]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/SQL_Access_Advisor/sh export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin cp * $ORACLE_HOME/demo/schema/sales_history sqlplus / as sysdba <
ECHO ON FEEDBACK 1 NUMWIDTH 10 LINESIZE 8000



Creating OLAP metadata ... <<<<< CREATE CWMLite Metadata for the Sales History Schema >>>>> … <<<<< FINAL PROCESSING >>>>> - Changes have been committed

Practice 9-1: Using Hints (continued) SET SET SET SET

TRIMSPOOL ON TAB OFF PAGESIZE 100 LONG 1000

CONNECT / AS SYSDBA alter user sh identified by sh account unlock; revoke dba from sh;

exit; FIN!

25) In the fifth case, you retrieve the first rows of your query as fast as possible. Connect to the SQL*Plus session as the SYS user and ensure that you set the following SQL*Plus environment variables: timing on autotrace on pagesize 200 linesize 200 [oracle@edrsr33p1-orcl Hints]$ sqlplus / as sysdba SQL*Plus: Release 11.1.0.6.0 - Production on Tue Apr 29 21:02:19 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> set timing on autotrace on pagesize 200 linesize 200 SQL>

26) From the same SQL*Plus session, execute the following query. Based on the fact that you want to retrieve the first 10 rows as fast as possible, what do you observe? SELECT employee_id, department_name FROM hr.employees e, hr.departments d WHERE e.department_id = d.department_id; a) It takes a bit of time before the result starts to be printed on the screen. This is because a merge join is used. It needs to sort all data before producing rows.



@sh_main sh example temp oracle /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/ /home/oracle/ v3

SQL> SELECT employee_id, department_name FROM hr.employees e, hr.departments d WHERE e.department_id = d.department_id; 2 3 EMPLOYEE_ID DEPARTMENT_NAME ----------- -----------------------------200 Administration 201 Marketing 202 Marketing 114 Purchasing 115 Purchasing 116 Purchasing 117 Purchasing … 113 Finance 205 Accounting 206 Accounting 106 rows selected. Elapsed: 00:00:00.09 Execution Plan ---------------------------------------------------------Plan hash value: 1343509718 ------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 106 | 2438 | 6 (17)| 00:00:01 | | 1 | MERGE JOIN | | 106 | 2438 | 6 (17)| 00:00:01 | | 2 | TABLE ACCESS BY INDEX ROWID| DEPARTMENTS | 27 | 432 | 2 (0)| 00:00:01 | | 3 | INDEX FULL SCAN | DEPT_ID_PK | 27 | | 1 (0)| 00:00:01 | |* 4 | SORT JOIN | | 107 | 749 | 4 (25)| 00:00:01 | | 5 | TABLE ACCESS FULL | EMPLOYEES | 107 | 749 | 3 (0)| 00:00:01 | ------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------4 - access("E"."DEPARTMENT_ID"="D"."DEPARTMENT_ID") filter("E"."DEPARTMENT_ID"="D"."DEPARTMENT_ID")





27) Using a hint, how can you ensure that the previous query starts fetching rows faster? Test your solution. a) Using the FIRST_ROWS(10) hint, a nested loop is chosen by the optimizer. It is faster to retrieve the first rows. SQL> SELECT /*+ FIRST_ROWS(10) */ employee_id, department_name FROM hr.employees e, hr.departments d WHERE e.department_id = d.department_id; 2 3 EMPLOYEE_ID DEPARTMENT_NAME ----------- -----------------------------200 Administration 201 Marketing 202 Marketing 114 Purchasing 115 Purchasing 116 Purchasing … 112 Finance 113 Finance 205 Accounting 206 Accounting 106 rows selected. Elapsed: 00:00:00.02 Execution Plan ---------------------------------------------------------Plan hash value: 1021246405 -------------------------------------------------------------------------------------------------




| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 10 | 230 | 3 (0)| 00:00:01 | | 1 | NESTED LOOPS | | | | | | | 2 | NESTED LOOPS | | 10 | 230 | 3 (0)| 00:00:01 | | 3 | TABLE ACCESS FULL | DEPARTMENTS | 25 | 400 | 2 (0)| 00:00:01 | |* 4 | INDEX RANGE SCAN | EMP_DEPARTMENT_IX | 8 | | 0 (0)| 00:00:01 | | 5 | TABLE ACCESS BY INDEX ROWID| EMPLOYEES | 3 | 21 | 1 (0)| 00:00:01 | ------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------4 - access("E"."DEPARTMENT_ID"="D"."DEPARTMENT_ID")








Practice 10-1: Tracing Applications In this practice, you define a service and use it to generate traces. You then interpret generated trace files. You can find all needed script files for this lab in your $HOME/solutions/Application_Tracing directory. 1) Initialize your environment be executing the at_setup.sh script from a terminal session connected as the oracle user. [oracle@edrsr33p1-orcl Application_Tracing]$ ./at_setup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Fri Apr 4 20:25:55 2008 All rights reserved.

Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> drop user trace cascade; drop user trace cascade * ERROR at line 1: ORA-01918: user 'TRACE' does not exist

SQL> SQL> create user trace identified by trace default tablespace users temporary tablespace temp; User created. SQL> SQL> grant connect, resource, dba to trace; Grant succeeded. SQL> SQL> SQL> drop tablespace tracetbs including contents and datafiles; drop tablespace tracetbs including contents and datafiles * ERROR at line 1: ORA-00959: tablespace 'TRACETBS' does not exist

SQL> SQL> drop tablespace tracetbs3 including contents and datafiles; drop tablespace tracetbs3 including contents and datafiles * ERROR at line 1: ORA-00959: tablespace 'TRACETBS3' does not exist




Practice 10-1: Tracing Applications (continued) SQL> SQL> create tablespace tracetbs 2 datafile '/u01/app/oracle/oradata/orcl/tracetbs.dbf' size 100m 3 extent management local uniform size 40k; Tablespace created. SQL> SQL> create tablespace tracetbs3 2 datafile '/u01/app/oracle/oradata/orcl/tracetbs3.dbf' size 100m 3 extent management local uniform size 10m;

SQL> SQL> SQL> connect trace/trace Connected. SQL> SQL> drop table sales purge; drop table sales purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> SQL> create table sales as select * from sh.sales; Table created. SQL> SQL> SQL> drop table sales2 purge; drop table sales2 purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> SQL> create table sales2 tablespace tracetbs as select * from sh.sales where 1=2; Table created. SQL> SQL> drop table sales3 purge; drop table sales3 purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL>



Tablespace created.

Practice 10-1: Tracing Applications (continued) SQL> create table sales3 tablespace tracetbs3 as select * from sh.sales where 1=2; Table created. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Application_Tracing]$

#!/bin/bash cd /home/oracle/solutions/Application_Tracing export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @at_setup.sql -------------------------------------------------------------set echo on drop user trace cascade; create user trace identified by trace default tablespace users temporary tablespace temp; grant connect, resource, dba to trace;

drop tablespace tracetbs including contents and datafiles; drop tablespace tracetbs3 including contents and datafiles; create tablespace tracetbs datafile '/u01/app/oracle/oradata/orcl/tracetbs.dbf' size 100m extent management local uniform size 40k; create tablespace tracetbs3 datafile '/u01/app/oracle/oradata/orcl/tracetbs3.dbf' size 100m extent management local uniform size 10m;

connect trace/trace drop table sales purge;



--------------------------------------------------------------

Practice 10-1: Tracing Applications (continued) create table sales as select * from sh.sales;

drop table sales2 purge; create table sales2 tablespace tracetbs as select * from sh.sales where 1=2; drop table sales3 purge; create table sales3 tablespace tracetbs3 as select * from sh.sales where 1=2;

2) Before you can use a service in your applications, you have to make sure this service is available from the tnsnames.ora file you use to connect to your database. Modify this file to make sure it references a service called TRACESERV. You can use the add_traceserv_tns.sh script to help you in this task. TRACESERV = (DESCRIPTION = (ADDRESS = (PROTOCOL = TCP)(HOST = node)(PORT = 1521)) (CONNECT_DATA = (SERVER = DEDICATED) (SERVICE_NAME = TRACESERV) ) ) [oracle@edrsr33p1-orcl Application_Tracing]$ ./add_traceserv_tns.sh [oracle@edrsr33p1-orcl Application_Tracing]$ -------------------------------------------------------------#!/bin/ksh y=`hostname` DBNAME=orcl sed 's/NODE/'$y'/' /home/oracle/solutions/Application_Tracing/wrong_tnstraceserv.ora > /home/oracle/solutions/Application_Tracing/tnstraceserv.ora cp /u01/app/oracle/product/11.1.0/db_1/network/admin/tnsnames.ora /u01/app/oracle/product/11.1.0/db_1/network/admin/tnsnames.ora.bak1 cat /home/oracle/solutions/Application_Tracing/tnstraceserv.ora >> /u01/app/oracle/product/11.1.0/db_1/network/admin/tnsnames.ora -------------------------------------------------------------TRACESERV = (DESCRIPTION = (ADDRESS = (PROTOCOL = TCP)(HOST = NODE)(PORT = 1521)) (CONNECT_DATA =



exit;

Practice 10-1: Tracing Applications (continued) (SERVER = DEDICATED) (SERVICE_NAME = TRACESERV) ) )

3) You now need to declare the TRACESERV service in your database. So connect to your database instance as the SYS user using a SQL*Plus session. [oracle@edrsr33p1-orcl Application_Tracing]$ sqlplus / as sysdba SQL*Plus: Release 11.1.0.6.0 - Production on Fri Apr 4 20:26:15 2008 All rights reserved.


4) In your SQL*Plus session, create a new service called TRACESERV with the same network name. SQL> @add_traceserv_db SQL> SQL> select name from dba_services; NAME ---------------------------------------------------------------SYS$BACKGROUND SYS$USERS seeddataXDB seeddata orclXDB orcl 6 rows selected. SQL> SQL> exec DBMS_SERVICE.CREATE_SERVICE('TRACESERV','TRACESERV'); PL/SQL procedure successfully completed. SQL> SQL> select name from dba_services; NAME ---------------------------------------------------------------SYS$BACKGROUND SYS$USERS seeddataXDB seeddata orclXDB




Practice 10-1: Tracing Applications (continued) orcl TRACESERV 7 rows selected. SQL> SQL> -------------------------------------------------------------set echo on select name from dba_services;

select name from dba_services;

5) From the same SQL*Plus session, start the TRACESERV service. SQL> @start_traceserv SQL> set echo on SQL> SQL> show parameter service_names NAME TYPE VALUE ------------------------------------ ----------- ----------------------------service_names string SQL> SQL> exec DBMS_SERVICE.START_SERVICE('TRACESERV'); PL/SQL procedure successfully completed. SQL> SQL> show parameter service_names NAME TYPE VALUE ------------------------------------ ----------- ----------------------------service_names string TRACESERV SQL> SQL> -------------------------------------------------------------set echo on show parameter service_names exec DBMS_SERVICE.START_SERVICE('TRACESERV'); show parameter service_names



exec DBMS_SERVICE.CREATE_SERVICE('TRACESERV','TRACESERV');

Practice 10-1: Tracing Applications (continued) 6) Exit from your SQL*Plus session. SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Application_Tracing]$

7) At this point, open a browser window and connect to Enterprise Manager Database Control as the SYS user. Ensure that you navigate to the Top Services page. a) Log in to Enterprise Manager as the SYS user. c) On the Performance page, click the Top Consumers link in the Additional Monitoring links section of the page. d) On the Top Consumers page, click the Top Services tab. This takes you to the Top Services page. 8) You now execute seven workload scripts that are traced. All workload scripts run under the TRACESERV service. Your goal is to analyze the generated trace files to interpret what happens in the seven cases. From your terminal session, execute the run_tracep0.sh script. This script is used to trigger the generation of statistics for your TRACESERV service so it can be viewed from within Enterprise Manager. As soon as you start the execution of the run_tracep0.sh script, move to the next step of this lab. [oracle@edrsr33p1-orcl Application_Tracing]$ ./run_tracep0.sh SQL*Plus: Release 11.1.0.6.0 - Production on Fri Apr 4 20:28:40 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> connect trace/trace@TRACESERV Connected. SQL> SQL> alter session set tracefile_identifier='mytraceP0'; Session altered. SQL> SQL> set termout off SQL> SQL> exit;



b) On the Database Home page, click the Performance tab.

Practice 10-1: Tracing Applications (continued) Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Application_Tracing]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Application_Tracing export ORACLE_SID=orcl

export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @run_tracep0.sql -------------------------------------------------------------set echo on connect trace/trace@TRACESERV alter session set tracefile_identifier='mytraceP0'; set termout off select select select select select select select select select select select select select select select select select select select select

count(*) count(*) count(*) count(*) count(*) count(*) count(*) count(*) count(*) count(*) count(*) count(*) count(*) count(*) count(*) count(*) count(*) count(*) count(*) count(*)

from from from from from from from from from from from from from from from from from from from from

dba_objects; dba_objects; dba_objects; dba_objects; dba_objects; dba_objects; dba_objects; dba_objects; dba_objects; dba_objects; dba_objects; dba_objects; dba_objects; dba_objects; dba_objects; dba_objects; dba_objects; dba_objects; dba_objects; dba_objects;

exec dbms_lock.sleep(60); set termout on exit;




Practice 10-1: Tracing Applications (continued) 9) Go back to the Top Consumers page in your Enterprise Manager session. Wait until you see the TRACESERV service in the Active Services table, and enable tracing for that service. a) When you see TRACESERV in the Active Services table on the Top Services page, select it, and click the Enable SQL Trace button. b) On the Enable SQL Trace page, make sure Waits is set to TRUE, and Binds is set to FALSE. Click OK.

10) When tracing for TRACESERV is enabled, execute the run_tracep1.sh script from your terminal session. Observe your screen. [oracle@edrsr33p1-orcl Application_Tracing]$ ./run_tracep1.sh SQL*Plus: Release 11.1.0.6.0 - Production on Fri Apr 4 20:29:48 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> connect trace/trace@TRACESERV Connected. SQL> SQL> alter session set workarea_size_policy=manual; Session altered. SQL> SQL> alter session set sort_area_size=50000; Session altered. SQL> SQL> alter session set hash_area_size=5000; Session altered. SQL> SQL> SQL> alter session set tracefile_identifier='mytraceP1'; Session altered. SQL> SQL> SQL> set timing on



c) Back to the Top Services page, you should see a confirmation message near the top of the Top Consumers page.

Practice 10-1: Tracing Applications (continued) SQL> SQL> select /*+ ORDERED USE_HASH(s2) */ count(*) from sales s1, sales s2 where s1.cust_id=s2.cust_id;

Elapsed: 00:01:19.25 SQL> SQL> SQL> SQL> connect trace/trace@TRACESERV Connected. SQL> SQL> alter session set tracefile_identifier='mytraceS1'; Session altered. Elapsed: 00:00:00.00 SQL> SQL> set timing on SQL> SQL> select /*+ ORDERED USE_HASH(s2) S1 */ count(*) from sales s1, sales s2 where s1.cust_id=s2.cust_id; COUNT(*) ---------172878975 Elapsed: 00:00:40.19 SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Application_Tracing]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Application_Tracing export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @run_tracep1.sql --------------------------------------------------------------



COUNT(*) ---------172878975

Practice 10-1: Tracing Applications (continued) [oracle@edrsr33p1-orcl Application_Tracing]$ cat run_tracep1.sql set echo on connect trace/trace@TRACESERV alter session set workarea_size_policy=manual; alter session set sort_area_size=50000; alter session set hash_area_size=5000;

set timing on select /*+ ORDERED USE_HASH(s2) */ count(*) from sales s1, sales s2 where s1.cust_id=s2.cust_id;

connect trace/trace@TRACESERV alter session set tracefile_identifier='mytraceS1'; set timing on select /*+ ORDERED USE_HASH(s2) S1 */ count(*) from sales s1, sales s2 where s1.cust_id=s2.cust_id; exit;

11) Execute the run_tracep2.sh script from your terminal session. Observe your screen. [oracle@edrsr33p1-orcl Application_Tracing]$ ./run_tracep2.sh SQL*Plus: Release 11.1.0.6.0 - Production on Fri Apr 4 20:31:57 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> connect trace/trace@TRACESERV Connected. SQL> SQL> alter session set tracefile_identifier='mytraceP2'; Session altered.



alter session set tracefile_identifier='mytraceP1';

SQL> SQL> set timing on SQL> SQL> declare 2 c number := dbms_sql.open_cursor; 3 oname varchar2(50); 4 ignore integer; 5 begin 6 for i in 1 .. 5000 loop 7 dbms_sql.parse(c,'select object_name from dba_objects where object_id = '||i , dbms_sql.native); -- use literal 8 dbms_sql.define_column(c, 1, oname, 50); 9 ignore := dbms_sql.execute(c); 10 if dbms_sql.fetch_rows(c)>0 then 11 dbms_sql.column_value(c, 1, oname); 12 end if; 13 end loop; 14 dbms_sql.close_cursor(c); 15 end; 16 / PL/SQL procedure successfully completed. Elapsed: 00:00:49.36 SQL> SQL> SQL> SQL> connect trace/trace@TRACESERV Connected. SQL> SQL> alter session set tracefile_identifier='mytraceS2'; Session altered. Elapsed: 00:00:00.00 SQL> SQL> declare 2 c number := dbms_sql.open_cursor; 3 oname varchar2(50); 4 ignore integer; 5 begin 6 dbms_sql.parse(c,'select object_name from dba_objects where object_id = :y' , dbms_sql.native); -- use bind var 7 for i in 1 .. 5000 loop 8 dbms_sql.bind_variable(c,':y',i); 9 dbms_sql.define_column(c, 1, oname, 50); 10 ignore := dbms_sql.execute(c); 11 if dbms_sql.fetch_rows(c)>0 then 12 dbms_sql.column_value(c, 1, oname); 13 end if; 14 end loop; 15 dbms_sql.close_cursor(c); 16 end; 17 / PL/SQL procedure successfully completed.



Practice 10-1: Tracing Applications (continued)

Practice 10-1: Tracing Applications (continued) Elapsed: 00:00:00.86 SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Application_Tracing]$ -------------------------------------------------------------#!/bin/bash

export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @run_tracep2.sql -------------------------------------------------------------set echo on connect trace/trace@TRACESERV alter session set tracefile_identifier='mytraceP2'; set timing on declare c number := dbms_sql.open_cursor; oname varchar2(50); ignore integer; begin for i in 1 .. 5000 loop dbms_sql.parse(c,'select object_name from dba_objects where object_id = '||i , dbms_sql.native); -- use literal dbms_sql.define_column(c, 1, oname, 50); ignore := dbms_sql.execute(c); if dbms_sql.fetch_rows(c)>0 then dbms_sql.column_value(c, 1, oname); end if; end loop; dbms_sql.close_cursor(c); end; /

connect trace/trace@TRACESERV



cd /home/oracle/solutions/Application_Tracing


declare c number := dbms_sql.open_cursor; oname varchar2(50); ignore integer; begin dbms_sql.parse(c,'select object_name from dba_objects where object_id = :y' , dbms_sql.native); -- use bind var for i in 1 .. 5000 loop dbms_sql.bind_variable(c,':y',i); dbms_sql.define_column(c, 1, oname, 50); ignore := dbms_sql.execute(c); if dbms_sql.fetch_rows(c)>0 then dbms_sql.column_value(c, 1, oname); end if; end loop; dbms_sql.close_cursor(c); end; / exit;



Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> connect trace/trace@TRACESERV Connected. SQL> SQL> alter session set tracefile_identifier='mytraceP3'; Session altered. SQL> SQL> update sales set amount_sold=20000 where prod_id=13 and cust_id=987; 2 rows updated. SQL> SQL> commit;



alter session set tracefile_identifier='mytraceS2';

Practice 10-1: Tracing Applications (continued) Commit complete. SQL> SQL> SQL> connect trace/trace Connected. SQL> SQL> create index sales_prod_cust_indx on sales(prod_id,cust_id);

SQL> SQL> connect trace/trace@TRACESERV Connected. SQL> SQL> alter session set tracefile_identifier='mytraceS3'; Session altered. SQL> SQL> update sales set amount_sold=30000 where prod_id=13 and cust_id=987; 2 rows updated. SQL> SQL> commit; Commit complete. SQL> SQL> connect trace/trace Connected. SQL> SQL> drop index sales_prod_cust_indx; Index dropped. SQL> SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Application_Tracing]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Application_Tracing export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1



Index created.

Practice 10-1: Tracing Applications (continued) export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @run_tracep3.sql -------------------------------------------------------------set echo on connect trace/trace@TRACESERV

update sales set amount_sold=20000 where prod_id=13 and cust_id=987; commit;

connect trace/trace create index sales_prod_cust_indx on sales(prod_id,cust_id); connect trace/trace@TRACESERV alter session set tracefile_identifier='mytraceS3'; update sales set amount_sold=30000 where prod_id=13 and cust_id=987; commit; connect trace/trace drop index sales_prod_cust_indx;

exit;






alter session set tracefile_identifier='mytraceP3';

Practice 10-1: Tracing Applications (continued) SQL> connect trace/trace@TRACESERV Connected. SQL> SQL> alter session set tracefile_identifier='mytraceP4'; Session altered.

set timing on DECLARE TYPE SalesCurTyp IS REF CURSOR; v_sales_cursor SalesCurTyp; sales_record sh.sales%ROWTYPE; v_stmt_str VARCHAR2(200); BEGIN -- Dynamic SQL statement with placeholder: v_stmt_str := 'select * from sh.sales where amount_sold>0'; -- Open cursor and specify bind argument in USING clause: OPEN v_sales_cursor FOR v_stmt_str; -- Fetch rows from result set one at a time: LOOP FETCH v_sales_cursor INTO sales_record; EXIT WHEN v_sales_cursor%NOTFOUND; END LOOP; -- Close cursor: CLOSE v_sales_cursor; END; /

PL/SQL procedure successfully completed. Elapsed: 00:00:26.84 SQL> SQL> SQL> connect trace/trace@TRACESERV Connected. SQL> SQL> alter session set tracefile_identifier='mytraceS4'; Session altered. Elapsed: 00:00:00.00 SQL> SQL> set timing on SQL> SQL> DECLARE 2 TYPE SalesCurTyp IS REF CURSOR; 3 TYPE SalesList IS TABLE OF sh.sales%ROWTYPE; 4 v_sales_cursor SalesCurTyp; 5 sales_List SalesList; 6 v_stmt_str VARCHAR2(200); 7 BEGIN 8 -- Dynamic SQL statement with placeholder:



SQL> SQL> SQL> SQL> 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

9 v_stmt_str := 'select /* S4 */ * from sh.sales where amount_sold>0'; 10 11 -- Open cursor: 12 OPEN v_sales_cursor FOR v_stmt_str; 13 14 -- Fetch rows from result set one at a time: 15 LOOP 16 FETCH v_sales_cursor BULK COLLECT INTO Sales_List LIMIT 10000; 17 EXIT WHEN v_sales_cursor%NOTFOUND; 18 END LOOP; 19 20 -- Close cursor: 21 CLOSE v_sales_cursor; 22 END; 23 / PL/SQL procedure successfully completed. Elapsed: 00:00:02.09 SQL> SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Application_Tracing]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Application_Tracing export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @run_tracep4.sql -------------------------------------------------------------set echo on connect trace/trace@TRACESERV alter session set tracefile_identifier='mytraceP4'; set timing on DECLARE TYPE SalesCurTyp

IS REF CURSOR;




Practice 10-1: Tracing Applications (continued) v_sales_cursor SalesCurTyp; sales_record sh.sales%ROWTYPE; v_stmt_str VARCHAR2(200); BEGIN -- Dynamic SQL statement with placeholder: v_stmt_str := 'select * from sh.sales where amount_sold>0'; -- Open cursor and specify bind argument in USING clause: OPEN v_sales_cursor FOR v_stmt_str;

-- Close cursor: CLOSE v_sales_cursor; END; /

connect trace/trace@TRACESERV alter session set tracefile_identifier='mytraceS4'; set timing on DECLARE TYPE SalesCurTyp IS REF CURSOR; TYPE SalesList IS TABLE OF sh.sales%ROWTYPE; v_sales_cursor SalesCurTyp; sales_List SalesList; v_stmt_str VARCHAR2(200); BEGIN -- Dynamic SQL statement with placeholder: v_stmt_str := 'select /* S4 */ * from sh.sales where amount_sold>0'; -- Open cursor: OPEN v_sales_cursor FOR v_stmt_str; -- Fetch rows from result set one at a time: LOOP FETCH v_sales_cursor BULK COLLECT INTO Sales_List LIMIT 10000; EXIT WHEN v_sales_cursor%NOTFOUND; END LOOP; -- Close cursor: CLOSE v_sales_cursor; END; /

exit;



-- Fetch rows from result set one at a time: LOOP FETCH v_sales_cursor INTO sales_record; EXIT WHEN v_sales_cursor%NOTFOUND; END LOOP;

Practice 10-1: Tracing Applications (continued) 14) Execute the run_tracep5.sh script from your terminal session. Observe your screen. [oracle@edrsr33p1-orcl Application_Tracing]$ ./run_tracep5.sh SQL*Plus: Release 11.1.0.6.0 - Production on Fri Apr 4 20:33:59 2008 Copyright (c) 1982, 2007, Oracle.


SQL> SQL> connect trace/trace@TRACESERV Connected. SQL> SQL> alter session set tracefile_identifier='mytraceP5'; Session altered. SQL> SQL> insert into sales2 select * from sh.sales union all select * from sales; 1837686 rows created. SQL> commit; Commit complete. SQL> SQL> SQL> connect trace/trace@TRACESERV Connected. SQL> SQL> alter session set tracefile_identifier='mytraceS5'; Session altered. SQL> SQL> insert into sales3 select * from sh.sales union all select * from sales; 1837686 rows created. SQL> commit; Commit complete. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production




Practice 10-1: Tracing Applications (continued) With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Application_Tracing]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Application_Tracing export ORACLE_SID=orcl

export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @run_tracep5.sql -------------------------------------------------------------set echo on connect trace/trace@TRACESERV alter session set tracefile_identifier='mytraceP5'; insert into sales2 select * from sh.sales union all select * from sales; commit;

connect trace/trace@TRACESERV alter session set tracefile_identifier='mytraceS5'; insert into sales3 select * from sh.sales union all select * from sales; commit; exit;



SQL*Plus: Release 11.1.0.6.0 - Production on Fri Apr 4 20:34:26 2008 Copyright (c) 1982, 2007, Oracle.





Practice 10-1: Tracing Applications (continued) Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options

SQL> SQL> connect trace/trace SQL> SQL> connect trace/trace@TRACESERV Connected. SQL> SQL> update sales set amount_sold=amount_sold+1; Connected. SQL> SQL> alter session set tracefile_identifier='mytraceP6'; Session altered. SQL> SQL> exec dbms_lock.sleep(30); 918843 rows updated. SQL> SQL> exec dbms_lock.sleep(60); PL/SQL procedure successfully completed. SQL> SQL> set termout off Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Application_Tracing]$ PL/SQL procedure successfully completed. SQL> SQL> rollback; Rollback complete. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining




Practice 10-1: Tracing Applications (continued) and Real Application Testing options [oracle@edrsr33p1-orcl Application_Tracing]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Application_Tracing export ORACLE_SID=orcl

export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @run_tracep6a.sql & sqlplus / as sysdba @run_tracep6b.sql --------------------------------------------------------------

set echo on connect trace/trace update sales set amount_sold=amount_sold+1; exec dbms_lock.sleep(60); rollback; exit; -------------------------------------------------------------set echo on connect trace/trace@TRACESERV alter session set tracefile_identifier='mytraceP6'; exec dbms_lock.sleep(30); set termout off select cust_id, sum(amount_sold) from sales group by cust_id order by cust_id; set tournout on exit;




Practice 10-1: Tracing Applications (continued) 16) Execute the run_tracep7.sh script from your terminal session. Observe your screen. [oracle@edrsr33p1-orcl Application_Tracing]$ ./run_tracep7.sh SQL*Plus: Release 11.1.0.6.0 - Production on Fri Apr 4 20:36:10 2008 Copyright (c) 1982, 2007, Oracle.


SQL> SQL> connect trace/trace@TRACESERV Connected. SQL> SQL> alter session set tracefile_identifier='mytraceP7'; Session altered. SQL> SQL> declare 2 c number := dbms_sql.open_cursor; 3 custid number; 4 amount number; 5 ignore integer; 6 begin 7 dbms_sql.parse(c,'select cust_id, sum(amount_sold) from sales where cust_id=2 group by cust_id order by cust_id' , dbms_sql.native); -- use bind var 8 dbms_sql.define_column(c, 1, custid); 9 dbms_sql.define_column(c, 2, amount); 10 ignore := dbms_sql.execute(c); 11 if dbms_sql.fetch_rows(c)>0 then 12 dbms_sql.column_value(c, 1, custid); 13 dbms_sql.column_value(c, 2, amount); 14 end if; 15 end; 16 / PL/SQL procedure successfully completed. SQL> SQL> connect trace/trace Connected. SQL> SQL> create index sales_cust_indx on sales(cust_id); Index created. SQL> SQL> exit;




Practice 10-1: Tracing Applications (continued) Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Application_Tracing]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Application_Tracing export ORACLE_SID=orcl

export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba @run_tracep7.sql -------------------------------------------------------------set echo on connect trace/trace@TRACESERV alter session set tracefile_identifier='mytraceP7'; declare c number := dbms_sql.open_cursor; custid number; amount number; ignore integer; begin dbms_sql.parse(c,'select cust_id, sum(amount_sold) from sales where cust_id=2 group by cust_id order by cust_id' , dbms_sql.native); -- use bind var dbms_sql.define_column(c, 1, custid); dbms_sql.define_column(c, 2, amount); ignore := dbms_sql.execute(c); if dbms_sql.fetch_rows(c)>0 then dbms_sql.column_value(c, 1, custid); dbms_sql.column_value(c, 2, amount); end if; end; / connect trace/trace create index sales_cust_indx on sales(cust_id); exit;

17) Disable tracing for your database.




Practice 10-1: Tracing Applications (continued) a) Go back to the Top Services page in your Enterprise Manager session. b) Ensure that TRACESERV is selected, and click the Disable SQL trace button. c) Back to the Top Services page, you should see a confirmation message near the top of the Top Consumers page.

[oracle@edrsr33p1-orcl Application_Tracing]$ ./show_mytraces.sh orcl_ora_19237_mytraceP0.trc orcl_ora_19237_mytraceP0.trm orcl_ora_19313_mytraceP1.trc orcl_ora_19313_mytraceP1.trm orcl_ora_19355_mytraceS1.trc orcl_ora_19355_mytraceS1.trm orcl_ora_19382_mytraceP2.trc orcl_ora_19382_mytraceP2.trm orcl_ora_19467_mytraceS2.trc orcl_ora_19467_mytraceS2.trm orcl_ora_19474_mytraceP3.trc orcl_ora_19474_mytraceP3.trm orcl_ora_19503_mytraceS3.trc orcl_ora_19503_mytraceS3.trm orcl_ora_19534_mytraceP4.trc orcl_ora_19534_mytraceP4.trm orcl_ora_19549_mytraceS4.trc orcl_ora_19549_mytraceS4.trm orcl_ora_19558_mytraceP5.trc orcl_ora_19558_mytraceP5.trm orcl_ora_19568_mytraceS5.trc orcl_ora_19568_mytraceS5.trm orcl_ora_19583_mytraceP6.trc orcl_ora_19583_mytraceP6.trm orcl_ora_19634_mytraceP7.trc orcl_ora_19634_mytraceP7.trm [oracle@edrsr33p1-orcl Application_Tracing]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Application_Tracing ls /u01/app/oracle/diag/rdbms/orcl/orcl/trace | grep mytrace

19) After you identify the location of those trace files, merge their content into one file called mytrace.trc located in your $HOME/solutions/Application_Tracing directory. [oracle@edrsr33p1-orcl Application_Tracing]$ ./merge_traces.sh [oracle@edrsr33p1-orcl Application_Tracing]$ --------------------------------------------------------------



18) Try to find out all the trace files that were generated to handle the previous seven cases.

Practice 10-1: Tracing Applications (continued) #!/bin/bash cd /home/oracle/solutions/Application_Tracing export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin

20) Use tkprof over the mytrace.trc file to generate a compiled trace output called myreport.txt located into your $HOME/solutions/Application_Tracing directory. [oracle@edrsr33p1-orcl Application_Tracing]$ ./tkprof_traces.sh TKPROF: Release 11.1.0.6.0 - Production on Fri Apr 4 20:37:27 2008 Copyright (c) 1982, 2007, Oracle.


[oracle@edrsr33p1-orcl Application_Tracing]$ [oracle@edrsr33p1-orcl Application_Tracing]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Application_Tracing export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin tkprof mytrace.trc myreport.txt

21) In addition, run TKPROF over the trace file that was generated for case 7 (step 16) with the EXPLAIN option set to your TRACE account. [oracle@edrsr33p1-orcl Application_Tracing]$ tkprof /u01/app/oracle/diag/rdbms/orcl/orcl/trace/*mytraceP7.trc myreport2.txt explain=trace/trace TKPROF: Release 11.1.0.6.0 - Production on Fri Apr 4 20:40:22 2008 Copyright (c) 1982, 2007, Oracle.




trcsess output=mytrace.trc service=TRACESERV /u01/app/oracle/diag/rdbms/orcl/orcl/trace/*.trc

Practice 10-1: Tracing Applications (continued) [oracle@edrsr33p1-orcl Application_Tracing]$ [oracle@edrsr33p1-orcl Application_Tracing]$

a) This case tries to illustrate the consequences of using manually sized SQL area parameters, such as HASH_AREA_SIZE. The first statement was executed using a very small HASH_AREA_SIZE value. The immediate consequence was the number of temporary segments needed to execute the statement. Later, the same statement was executed, but this time using the default SQL area parameters, which were sized automatically by the system to handle the needs. You can see a high disk value as well as a high number of waits for temporary segments for the first execution, compared to the second one. select /*+ ORDERED USE_HASH(s2) */ count(*) from sales s1, sales s2 where s1.cust_id=s2.cust_id

call count rows ------- --------------Parse 1 0 Execute 1 0 Fetch 2 1 ------- --------------total 4 1

cpu

elapsed

disk

query

current

-------- ---------- ---------- ---------- ---------0.00

0.00

0

2

0

0.00

0.00

0

0

0

78.23

79.16

806500

8874

0

-------- ---------- ---------- ---------- ---------78.23

79.16

806500

8876

0

Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 182 Rows Row Source Operation ------- --------------------------------------------------1 SORT AGGREGATE (cr=8874 pr=806500 pw=806500 time=0 us) 172878975 HASH JOIN (cr=8874 pr=806500 pw=806500 time=1723284 us cost=1392520 size=5737160286 card=220660011) 918843 TABLE ACCESS FULL SALES (cr=4437 pr=4433 pw=4433 time=7413 us cost=1363 size=14132716 card=1087132) 918843 TABLE ACCESS FULL SALES (cr=4437 pr=4433 pw=4433 time=7485 us cost=1363 size=14132716 card=1087132)

Elapsed times include waiting on following events: Event waited on Times Total Waited

Max. Wait



22) After this is done, interpret the trace generated for case 1 (step 10). What do you observe, and what are your conclusions?

---------------------------------------Waited ---------- ----------SQL*Net message to client 2 0.00 0.00 reliable message 1 0.00 0.00 enq: KO - fast object checkpoint 1 0.00 0.00 direct path read 86 0.00 0.00 direct path write temp 2524 0.00 0.00 direct path read temp 797634 0.00 1.70 SQL*Net message from client 2 0.00 0.00 ******************************************************************** ************

select /*+ ORDERED USE_HASH(s2) S1 */ count(*) from sales s1, sales s2 where s1.cust_id=s2.cust_id


cpu

elapsed

disk

query

current

-------- ---------- ---------- ---------- ---------0.00

0.00

0

2

0

0.00

0.00

0

0

0

40.02

40.14

10028

8874

0

-------- ---------- ---------- ---------- ---------40.03

40.14

10028

8876

Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 182 Rows Row Source Operation ------- --------------------------------------------------1 SORT AGGREGATE (cr=8874 pr=10028 pw=10028 time=0 us) 172878975 HASH JOIN (cr=8874 pr=10028 pw=10028 time=1430806 us cost=6891 size=5737160286 card=220660011) 918843 TABLE ACCESS FULL SALES (cr=4437 pr=4433 pw=4433 time=6837 us cost=1363 size=14132716 card=1087132) 918843 TABLE ACCESS FULL SALES (cr=4437 pr=4433 pw=4433 time=7084 us cost=1363 size=14132716 card=1087132)


0



Elapsed times include waiting on following events: Event waited on Times Max. Wait Total Waited ---------------------------------------Waited ---------- ----------SQL*Net message to client 2 0.00 0.00 direct path read 86 0.00 0.00 direct path write temp 166 0.00 0.00 direct path read temp 166 0.00 0.00 SQL*Net message from client 2 0.00 0.00 ******************************************************************** ************

23) Interpret the trace generated for case 2 (step 11). What do you observe, and what are your conclusions? a) For this case, the almost same statement was run 5000 times, but each time a different literal was used to execute the query. This caused the system to parse almost the same statement 5000 times, which is extremely inefficient although the time precision is too low to give accurate information about the parse time of each statement. However, another statement was also executed 5000 times, but this time using a bind variable. The statement was parsed only once, and executed 5000 times. This behavior is much more efficient than the previous one. select object_name from dba_objects where object_id = 1


cpu

elapsed

disk

query

-------- ---------- ---------- ---------- ---------0.01

0.01

0

0

0

0.00

0.00

0

0

0

0.00

0.00

0

3

0

-------- ---------- ---------- ---------- ---------0.01

0.01

0

3

Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 182 (recursive depth: 1) Rows

current

Row Source Operation


0



------- --------------------------------------------------0 VIEW DBA_OBJECTS (cr=3 pr=0 pw=0 time=0 us cost=5 size=158 card=2) 0 UNION-ALL (cr=3 pr=0 pw=0 time=0 us) 0 FILTER (cr=3 pr=0 pw=0 time=0 us) 0 NESTED LOOPS (cr=3 pr=0 pw=0 time=0 us cost=5 size=109 card=1) 0 NESTED LOOPS (cr=3 pr=0 pw=0 time=0 us cost=4 size=105 card=1) 0 TABLE ACCESS BY INDEX ROWID OBJ$ (cr=3 pr=0 pw=0 time=0 us cost=3 size=82 card=1) 1 INDEX RANGE SCAN I_OBJ1 (cr=2 pr=0 pw=0 time=0 us cost=2 size=0 card=1)(object id 36) 0 INDEX RANGE SCAN I_USER2 (cr=0 pr=0 pw=0 time=0 us cost=1 size=23 card=1)(object id 47) 0 INDEX RANGE SCAN I_USER2 (cr=0 pr=0 pw=0 time=0 us cost=1 size=4 card=1)(object id 47) 0 TABLE ACCESS BY INDEX ROWID IND$ (cr=0 pr=0 pw=0 time=0 us cost=2 size=8 card=1) 0 INDEX UNIQUE SCAN I_IND1 (cr=0 pr=0 pw=0 time=0 us cost=1 size=0 card=1)(object id 41) 0 NESTED LOOPS (cr=0 pr=0 pw=0 time=0 us cost=2 size=28 card=1) 0 INDEX FULL SCAN I_USER2 (cr=0 pr=0 pw=0 time=0 us cost=1 size=20 card=1)(object id 47) 0 INDEX RANGE SCAN I_OBJ4 (cr=0 pr=0 pw=0 time=0 us cost=1 size=8 card=1)(object id 39) 0 FILTER (cr=0 pr=0 pw=0 time=0 us) 0 NESTED LOOPS (cr=0 pr=0 pw=0 time=0 us cost=1 size=83 card=1) 0 INDEX FULL SCAN I_LINK1 (cr=0 pr=0 pw=0 time=0 us cost=0 size=79 card=1)(object id 134) 0 INDEX RANGE SCAN I_USER2 (cr=0 pr=0 pw=0 time=0 us cost=1 size=4 card=1)(object id 47) ******************************************************************** ************

select object_name from dba_objects where object_id = 2

call count rows ------- --------------Parse 1 0 Execute 1 0 Fetch 1 1 ------- ---------------

cpu

elapsed

disk

query

current

-------- ---------- ---------- ---------- ---------0.00

0.00

0

0

0

0.00

0.00

0

0

0

0.00

0.00

0

5

0

-------- ---------- ---------- ---------- ----------




Practice 10-1: Tracing Applications (continued) total 1

3

0.00

0.00

0

5

0

query

current

Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 182 (recursive depth: 1)

...


cpu

elapsed

disk

-------- ---------- ---------- ---------- ---------0.00

0.00

0

0

0

0.00

0.00

0

0

0

0.00

0.00

0

5

0

-------- ---------- ---------- ---------- ---------0.00

0.00

0

5

0

Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 182 (recursive depth: 1) Rows Row Source Operation ------- --------------------------------------------------1 VIEW DBA_OBJECTS (cr=5 pr=0 pw=0 time=0 us cost=5 size=158 card=2) 1 UNION-ALL (cr=5 pr=0 pw=0 time=0 us) 1 FILTER (cr=5 pr=0 pw=0 time=0 us) 1 NESTED LOOPS (cr=5 pr=0 pw=0 time=0 us cost=5 size=109 card=1) 1 NESTED LOOPS (cr=4 pr=0 pw=0 time=0 us cost=4 size=105 card=1) 1 TABLE ACCESS BY INDEX ROWID OBJ$ (cr=3 pr=0 pw=0 time=0 us cost=3 size=82 card=1) 1 INDEX RANGE SCAN I_OBJ1 (cr=2 pr=0 pw=0 time=0 us cost=2 size=0 card=1)(object id 36) 1 INDEX RANGE SCAN I_USER2 (cr=1 pr=0 pw=0 time=0 us cost=1 size=23 card=1)(object id 47) 1 INDEX RANGE SCAN I_USER2 (cr=1 pr=0 pw=0 time=0 us cost=1 size=4 card=1)(object id 47) 0 TABLE ACCESS BY INDEX ROWID IND$ (cr=0 pr=0 pw=0 time=0 us cost=2 size=8 card=1) 0 INDEX UNIQUE SCAN I_IND1 (cr=0 pr=0 pw=0 time=0 us cost=1 size=0 card=1)(object id 41)



select object_name from dba_objects where object_id = 5000


******************************************************************** ************

select object_name from dba_objects where object_id = :y


cpu

elapsed

disk

query

current

-------- ---------- ---------- ---------- ---------0.00

0.00

0

0

0

0.20

0.18

0

0

0

0.24

0.24

0

26837

0

-------- ---------- ---------- ---------- ---------0.45

0.43

0

26837

0

Misses in library cache during parse: 1 Misses in library cache during execute: 1 Optimizer mode: ALL_ROWS Parsing user id: 182 (recursive depth: 1) Rows ------0 card=2) 0 0 0 card=1)

Row Source Operation --------------------------------------------------VIEW DBA_OBJECTS (cr=3 pr=0 pw=0 time=0 us cost=5 size=158 UNION-ALL (cr=3 pr=0 pw=0 time=0 us) FILTER (cr=3 pr=0 pw=0 time=0 us) NESTED LOOPS (cr=3 pr=0 pw=0 time=0 us cost=5 size=109



0 NESTED LOOPS (cr=0 pr=0 pw=0 time=0 us cost=2 size=28 card=1) 0 INDEX FULL SCAN I_USER2 (cr=0 pr=0 pw=0 time=0 us cost=1 size=20 card=1)(object id 47) 0 INDEX RANGE SCAN I_OBJ4 (cr=0 pr=0 pw=0 time=0 us cost=1 size=8 card=1)(object id 39) 0 FILTER (cr=0 pr=0 pw=0 time=0 us) 0 NESTED LOOPS (cr=0 pr=0 pw=0 time=0 us cost=1 size=83 card=1) 0 INDEX FULL SCAN I_LINK1 (cr=0 pr=0 pw=0 time=0 us cost=0 size=79 card=1)(object id 134) 0 INDEX RANGE SCAN I_USER2 (cr=0 pr=0 pw=0 time=0 us cost=1 size=4 card=1)(object id 47)

0 NESTED LOOPS (cr=3 pr=0 pw=0 time=0 us cost=4 size=105 card=1) 0 TABLE ACCESS BY INDEX ROWID OBJ$ (cr=3 pr=0 pw=0 time=0 us cost=3 size=82 card=1) 1 INDEX RANGE SCAN I_OBJ1 (cr=2 pr=0 pw=0 time=0 us cost=2 size=0 card=1)(object id 36) 0 INDEX RANGE SCAN I_USER2 (cr=0 pr=0 pw=0 time=0 us cost=1 size=23 card=1)(object id 47) 0 INDEX RANGE SCAN I_USER2 (cr=0 pr=0 pw=0 time=0 us cost=1 size=4 card=1)(object id 47) 0 TABLE ACCESS BY INDEX ROWID IND$ (cr=0 pr=0 pw=0 time=0 us cost=2 size=8 card=1) 0 INDEX UNIQUE SCAN I_IND1 (cr=0 pr=0 pw=0 time=0 us cost=1 size=0 card=1)(object id 41) 0 NESTED LOOPS (cr=0 pr=0 pw=0 time=0 us cost=2 size=28 card=1) 0 INDEX FULL SCAN I_USER2 (cr=0 pr=0 pw=0 time=0 us cost=1 size=20 card=1)(object id 47) 0 INDEX RANGE SCAN I_OBJ4 (cr=0 pr=0 pw=0 time=0 us cost=1 size=8 card=1)(object id 39) 0 FILTER (cr=0 pr=0 pw=0 time=0 us) 0 NESTED LOOPS (cr=0 pr=0 pw=0 time=0 us cost=1 size=83 card=1) 0 INDEX FULL SCAN I_LINK1 (cr=0 pr=0 pw=0 time=0 us cost=0 size=79 card=1)(object id 134) 0 INDEX RANGE SCAN I_USER2 (cr=0 pr=0 pw=0 time=0 us cost=1 size=4 card=1)(object id 47) ******************************************************************** ************

24) Interpret the trace generated for case 3 (step 12). What do you observe, and what are your conclusions? a) If you look closely at this case, you see that you access the complete table to update only two rows. This is very inefficient and the alternate case is much better as it uses an index to speed up the retrieval of the rows that need to be updated. update sales set amount_sold=20000 where prod_id=13 and cust_id=987


cpu

elapsed

disk

query

current

-------- ---------- ---------- ---------- ---------0.00

0.00

0

1

0

0.09

0.09

2442

4441

4

0.00

0.00

0

0

0

-------- ---------- ---------- ---------- ---------0.09

0.10

2442

4442


4



Practice 10-1: Tracing Applications (continued) Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 182

Elapsed times include waiting on following events: Event waited on Times Max. Wait Total Waited ---------------------------------------Waited ---------- ----------db file scattered read 63 0.00 0.01 db file sequential read 3 0.00 0.00 SQL*Net message to client 1 0.00 0.00 SQL*Net message from client 1 0.00 0.00 ******************************************************************** ************

update sales set amount_sold=30000 where prod_id=13 and cust_id=987


cpu

elapsed

disk

query

-------- ---------- ---------- ---------- ---------0.00

0.00

0

2

0

0.00

0.00

0

3

3

0.00

0.00

0

0

0

-------- ---------- ---------- ---------- ---------0.00

0.00

0

5

Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 182 Rows

current



3


Rows Row Source Operation ------- --------------------------------------------------0 UPDATE SALES (cr=4441 pr=2442 pw=2442 time=0 us) 2 TABLE ACCESS FULL SALES (cr=4441 pr=2442 pw=2442 time=17 us cost=1366 size=4251 card=109)


Elapsed times include waiting on following events: Event waited on Times Max. Wait Total Waited ---------------------------------------Waited ---------- ----------SQL*Net message to client 1 0.00 0.00 SQL*Net message from client 1 0.00 0.00 ******************************************************************** ************

25) Interpret the trace generated for case 4 (step 13). What do you observe, and what are your conclusions? a) In this case, the first statement does not use the fetching mechanism appropriately. One fetch operation is done for every single row retrieved. This is also very inefficient. The alternate case is doing 92 fetches to retrieve the same amount of rows. This technique is called array fetch. select * from sh.sales where amount_sold>0


cpu

elapsed

disk

query

current

-------- ---------- ---------- ---------- ---------0.02

0.02

0

0

0

0.00

0.00

0

0

0

5.89

5.93

0

918944

0

-------- ---------- ---------- ---------- ---------5.92

5.95

0

918944

Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 182 (recursive depth: 1) Rows Row Source Operation ------- --------------------------------------------------918843 PARTITION RANGE ALL PARTITION: 1 28 (cr=918944 pr=0 pw=0 time=41095 us cost=547 size=26646447 card=918843) 918843 TABLE ACCESS FULL SALES PARTITION: 1 28 (cr=918944 pr=0 pw=0 time=27743 us cost=547 size=26646447 card=918843)


0


------- --------------------------------------------------0 UPDATE SALES (cr=3 pr=0 pw=0 time=0 us) 2 INDEX RANGE SCAN SALES_PROD_CUST_INDX (cr=3 pr=0 pw=0 time=2 us cost=3 size=78 card=2)(object id 75372)

Practice 10-1: Tracing Applications (continued) ******************************************************************** ************

select /* S4 */ * from sh.sales where amount_sold>0

cpu

elapsed

disk

query

current

-------- ---------- ---------- ---------- ---------0.00

0.00

0

0

0

0.00

0.00

0

0

0

2.06

2.06

0

1811

0

-------- ---------- ---------- ---------- ---------2.06

2.06

0

1811

0

Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 182 (recursive depth: 1) Rows Row Source Operation ------- --------------------------------------------------918843 PARTITION RANGE ALL PARTITION: 1 28 (cr=1811 pr=0 pw=0 time=21132 us cost=547 size=26646447 card=918843) 918843 TABLE ACCESS FULL SALES PARTITION: 1 28 (cr=1811 pr=0 pw=0 time=8617 us cost=547 size=26646447 card=918843) ******************************************************************** ************

26) Interpret the trace generated for case 5 (step 14). What do you observe, and what are your conclusions? a) Here, the first statement incurs too many recursive calls to allocate extents to the table. This is because the tablespace in which it is stored is not correctly set up for extent allocations. The alternate case is much better as you can see the number of disk values going way down compared to the first case. Also the number of recursive statements in the second case should be much lower than the first one. insert into sales2 select * from sh.sales union all select * from sales

call rows

count

cpu

elapsed

disk

query


current



Practice 10-1: Tracing Applications (continued) -------- ---------- ---------- ---------- ---------0.00

0.01

0

2

0

5.02

5.41

4432

28134

148866

0.00

0.00

0

0

0

-------- ---------- ---------- ---------- ---------5.02

5.42

4432

28136

148866

Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 182 Rows Row Source Operation ------- --------------------------------------------------0 LOAD TABLE CONVENTIONAL (cr=44323 pr=4433 pw=4433 time=0 us) 1837686 UNION-ALL (cr=6160 pr=4432 pw=4432 time=58107 us) 918843 PARTITION RANGE ALL PARTITION: 1 28 (cr=1719 pr=0 pw=0 time=21204 us cost=545 size=26646447 card=918843) 918843 TABLE ACCESS FULL SALES PARTITION: 1 28 (cr=1719 pr=0 pw=0 time=8395 us cost=545 size=26646447 card=918843) 918843 TABLE ACCESS FULL SALES (cr=4441 pr=4432 pw=4432 time=6976 us cost=1369 size=94580484 card=1087132)

Elapsed times include waiting on following events: Event waited on Times Max. Wait Total Waited ---------------------------------------Waited ---------- ----------db file scattered read 51 0.00 0.03 log file switch completion 2 0.00 0.00 log buffer space 8 0.09 0.23 SQL*Net message to client 1 0.00 0.00 SQL*Net message from client 1 0.00 0.00 ******************************************************************** ************ select file# from file$ where ts#=:1

call count rows ------- ---------------

cpu

elapsed

disk

query

current

-------- ---------- ---------- ---------- ----------



------- --------------Parse 1 0 Execute 1 1837686 Fetch 0 0 ------- --------------total 2 1837686

Practice 10-1: Tracing Applications (continued) Parse 1812 0 Execute 1812 0 Fetch 3624 1812 ------- --------------total 7248 1812

0.02

0.02

0

0

0

0.02

0.03

0

0

0

0.05

0.05

0

7242

0

-------- ---------- ---------- ---------- ---------0.11

0.10

0

7242

0

Rows Row Source Operation ------- --------------------------------------------------1 TABLE ACCESS FULL FILE$ (cr=4 pr=0 pw=0 time=0 us cost=2 size=6 card=1) ******************************************************************** ************

insert into sales3 select * from sh.sales union all select * from sales


cpu

elapsed

disk

query

-------- ---------- ---------- ---------- ---------0.00

0.00

0

1

0

3.64

5.13

1087

22471

77748

0.00

0.00

0

0

0

-------- ---------- ---------- ---------- ---------3.65

5.14

1087

22472

Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 182 Rows

current



77748


Misses in library cache during parse: 1 Misses in library cache during execute: 1 Optimizer mode: CHOOSE Parsing user id: SYS (recursive depth: 1)


Elapsed times include waiting on following events: Event waited on Times Max. Wait Total Waited ---------------------------------------Waited ---------- ----------buffer busy waits 3 0.00 0.00 undo segment extension 1 0.00 0.00 log file switch completion 5 0.08 0.12 log buffer space 30 0.15 1.24 db file scattered read 25 0.00 0.00 log file switch (private strand flush incomplete) 313 0.05 0.10 SQL*Net message to client 1 0.00 0.00 SQL*Net message from client 1 0.00 0.00 ******************************************************************** ************

27) Interpret the trace generated for case 6 (step 15). What do you observe, and what are your conclusions? a) This case is more difficult to understand. Here, you select a table that is entirely locked by another transaction. This forces the query to generate consistent read blocks for almost the entire table causing undo segments to be accessed. This is materialized by an important disk value, and almost no current blocks. select cust_id, sum(amount_sold) from sales group by cust_id order by cust_id

call count rows ------- --------------Parse 1 0

cpu

elapsed

disk

query

current

-------- ---------- ---------- ---------- ---------0.00

0.00

0

1


0


------- --------------------------------------------------0 LOAD TABLE CONVENTIONAL (cr=22544 pr=1087 pw=1087 time=0 us) 1837686 UNION-ALL (cr=6160 pr=1087 pw=1087 time=58277 us) 918843 PARTITION RANGE ALL PARTITION: 1 28 (cr=1719 pr=0 pw=0 time=21371 us cost=545 size=26646447 card=918843) 918843 TABLE ACCESS FULL SALES PARTITION: 1 28 (cr=1719 pr=0 pw=0 time=8407 us cost=545 size=26646447 card=918843) 918843 TABLE ACCESS FULL SALES (cr=4441 pr=1087 pw=1087 time=7141 us cost=1369 size=94580484 card=1087132)

Practice 10-1: Tracing Applications (continued) Execute 1 0 Fetch 472 7059 ------- --------------total 474 7059

0.00

0.00

0

0

0

2.38

2.39

5333

978282

0

-------- ---------- ---------- ---------- ---------2.39

2.39

5333

978283

0

Rows Row Source Operation ------- --------------------------------------------------7059 SORT GROUP BY (cr=978282 pr=5333 pw=5333 time=64 us cost=1422 size=28265432 card=1087132) 918843 TABLE ACCESS FULL SALES (cr=978282 pr=5333 pw=5333 time=17979 us cost=1369 size=28265432 card=1087132)

Elapsed times include waiting on following events: Event waited on Times Max. Wait Total Waited ---------------------------------------Waited ---------- ----------SQL*Net message to client 472 0.00 0.00 db file sequential read 3827 0.00 0.03 db file scattered read 37 0.00 0.01 latch: cache buffers lru chain 1 0.00 0.00 SQL*Net message from client 472 0.00 0.02 ******************************************************************** ************

28) Interpret the trace generated for case 7 (step 16). What do you observe, and what are your conclusions? a) For case 7, you should compare the content in myreport.txt with the content in myreport2.txt. You should see that an index was added after the first trace was generated. This situation can cause confusion especially if the trace does not contain an execution plan to begin with. This is what you can see from within myreport.txt: select cust_id, sum(amount_sold) from sales where cust_id=2 group by cust_id order by cust_id

call rows

count

cpu

elapsed

disk

query


current


Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 182

Practice 10-1: Tracing Applications (continued) -------- ---------- ---------- ---------- ---------0.00

0.00

0

1

0

0.00

0.00

0

0

0

0.05

0.05

0

4441

0

-------- ---------- ---------- ---------- ---------0.06

0.06

0

4442

0

Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 182 (recursive depth: 1) Rows Row Source Operation ------- --------------------------------------------------1 SORT GROUP BY NOSORT (cr=4441 pr=0 pw=0 time=0 us cost=1366 size=1872 card=72) 176 TABLE ACCESS FULL SALES (cr=4441 pr=0 pw=0 time=153 us cost=1366 size=1872 card=72)

******************************************************************** ************

b) This is what you see from myreport2.txt: SQL ID : 51xxq509gnbbc select cust_id, sum(amount_sold) from sales where cust_id=2 group by cust_id order by cust_id


cpu

elapsed

disk

query

current

-------- ---------- ---------- ---------- ---------0.00

0.00

0

1

0

0.00

0.00

0

0

0

0.05

0.05

0

4441

0

-------- ---------- ---------- ---------- ---------0.06

0.06

0

4442

Misses in library cache during parse: 1 Optimizer mode: ALL_ROWS Parsing user id: 182 (TRACE) (recursive depth: 1)


0


------- --------------Parse 1 0 Execute 1 0 Fetch 1 1 ------- --------------total 3 1

Practice 10-1: Tracing Applications (continued) Rows Row Source Operation ------- --------------------------------------------------1 SORT GROUP BY NOSORT (cr=4441 pr=0 pw=0 time=0 us cost=1366 size=1872 card=72) 176 TABLE ACCESS FULL SALES (cr=4441 pr=0 pw=0 time=153 us cost=1366 size=1872 card=72)

Execution Plan --------------------------------------------------SELECT STATEMENT MODE: ALL_ROWS SORT (GROUP BY NOSORT) TABLE ACCESS (BY INDEX ROWID) OF 'SALES' (TABLE) INDEX MODE: ANALYZED (RANGE SCAN) OF 'SALES_CUST_INDX' (INDEX)

Elapsed times include waiting on following events: Event waited on Times Max. Wait Total Waited ---------------------------------------Waited ---------- ----------SQL*Net message to client 1 0.00 0.00 SQL*Net message from client 1 0.00 0.00 ******************************************************************** ************

29) You can now clean up your environment by executing the at_cleanup.sh script from your terminal window. [oracle@edrsr33p1-orcl Application_Tracing]$ ./at_cleanup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Fri Apr 4 20:45:24 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> drop user trace cascade; User dropped. SQL> SQL> drop tablespace tracetbs including contents and datafiles; Tablespace dropped. SQL> SQL> drop tablespace tracetbs3 including contents and datafiles;



Rows ------0 1 176 0

Practice 10-1: Tracing Applications (continued) Tablespace dropped. SQL> SQL> exit; Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Application_Tracing]$ --------------------------------------------------------------

cd /home/oracle/solutions/Application_Tracing export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin rm /u01/app/oracle/diag/rdbms/orcl/orcl/trace/*mytrace*.* rm mytrace.trc rm myreport.txt rm myreport2.txt rm $ORACLE_HOME/network/admin/tnsnames.ora mv $ORACLE_HOME/network/admin/tnsnames.ora.bak1 $ORACLE_HOME/network/admin/tnsnames.ora sqlplus / as sysdba @at_cleanup.sql -------------------------------------------------------------set echo on drop user trace cascade; drop tablespace tracetbs including contents and datafiles; drop tablespace tracetbs3 including contents and datafiles; exit;



#!/bin/bash




Practice 11-1: Proactively Tuning High-Load SQL Statements In this practice, you use the SQL Tuning Advisor to help you tune problematic SQL statements. 1) Connect as SYSDBA through Database Control and navigate to the Performance tab of the Database Control Home page. On the Performance tabbed page, make sure that the View Data field is set to Real Time: 15 second Refresh. After this is done, open a terminal emulator window connected as the oracle user. When this is done, change your current directory to your lab directory: cd $HOME/solutions/SQL_Tuning_Advisor. Then enter the following command from the OS prompt: ./setup_dina.sh

[oracle@edrsr33p1-orcl SQL_Tuning_Advisor]$ ./setup_dina.sh PL/SQL procedure successfully completed.

Grant succeeded.

Session altered.



User altered.

User altered.

Index dropped. drop index sales_time_idx * ERROR at line 1: ORA-01418: specified index does not exist

Index created. [oracle@edrsr33p1-orcl SQL_Tuning_Advisor]$

-------------------------------------------------------------#!/bin/bash



[oracle@edrsr33p1-orcl SQL_Tuning_Advisor]$ ./setup_dina.sh

Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) cd /home/oracle/solutions/SQL_Tuning_Advisor export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus -s /NOLOG <
connect / as sysdba exec DBMS_WORKLOAD_REPOSITORY.CREATE_SNAPSHOT(); grant dba to SH; rem -- event to allow setting very short Flushing interval alter session set events '13508 trace name context forever, level 1';

rem -- change INTERVAL setting to 2 minutes rem -- change RETENTION setting to 6 hours (total of 180 snapshots) execute dbms_workload_repository.modify_snapshot_settings(interval => 2,retention => 360);

rem -- play with ADDM sensitiveness exec dbms_advisor.set_default_task_parameter('ADDM','DB_ACTIVITY_MIN',30) ;

alter user sh account unlock; alter user sh identified by sh; connect sh/sh drop index sales_time_bix; drop index sales_time_idx; create index sales_time_idx on sales(time_id) compute statistics;

EOF

2) After this is executed, execute the start_dinas.sh script by using the following command: ./start_dinas.sh This script starts the workload used for this lab.



set echo on

Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) [oracle@edrsr33p1-orcl SQL_Tuning_Advisor]$ ./start_dinas.sh Started stream with pid=30479 Started stream with pid=30480 Started stream with pid=30481 Started stream with pid=30482 Started stream with pid=30485 Started stream with pid=30486 [oracle@edrsr33p1-orcl SQL_Tuning_Advisor]$ -------------------------------------------------------------#!/bin/bash

export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin

STREAM_NUM=0 MAX_STREAM=6 PIDLST="" while [ $STREAM_NUM -lt $MAX_STREAM ]; do # one more let STREAM_NUM="STREAM_NUM+1" # start one more stream sqlplus -S sh/sh @dina.sql & # remember PID PIDLST="$! $PIDLST" echo "Started stream with pid=$!" done # # Save PID List # echo $PIDLST > /tmp/dina_pids -------------------------------------------------------------DECLARE n number; BEGIN for i in 1..1000 loop select /*+ ORDERED USE_NL(c) FULL(c) FULL(s)*/ count(*) into n from sales s, customers c



cd /home/oracle/solutions/SQL_Tuning_Advisor

Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) where c.cust_id = s.cust_id and CUST_FIRST_NAME='Dina' order by time_id; end loop; END; /

a) You should see that the workload activity goes up very quickly. Because the CPU used by the workload is very close to the maximum CPU available on your system, there must be an issue with this workload. Because the most important area corresponding to a wait class is the Other wait class, the issue must be associated to that class. Note that the snapshot interval is now around two minutes. 4) Fix the problem. a) The fastest way to determine the problem is by looking at an Automatic Database Diagnostic Monitor (ADDM) report analysis executed during the problematic period. Then, by following its analysis, ADDM should guide you through the process of fixing the problem. b) Using the Database Control Home page, there are two different ways to identify the correct ADDM analysis task: i) If the time corresponding to the problematic time period corresponds with the latest ADDM run detected by Database Control, you should find the link corresponding to the correct performance analysis directly in the Diagnostic Summary section of the Database Control Home page. Note that you should wait around 8 to 10 minutes before the Diagnostic Summary section is refreshed with the correct ADDM analysis. If you are in this case, click the link corresponding to the number of findings right next to the ADDM Findings row. This takes you to the corresponding Automatic Database Diagnostic Monitor (ADDM) page. ii) If not, you should open the Advisor Central page and search for the correct ADDM task. This is how you can retrieve the task from the Advisor Central page: (1) On the Database Control Home page, click the Advisor Central link. (2) On the Advisor Central page, in the search section, select ADDM from the Advisory Type drop-down list, and Last 24 Hours from the Advisor Runs drop-down list. (3) After this is done, click Go. (4) Then select the ADDM task corresponding to the time of the problematic period.



3) When the start_dinas.sh script completes, observe the Performance tabbed page for around 10 minutes (5 snapshot icons). What are your conclusions?

Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) (5) This takes you to the corresponding Automatic Database Diagnostic Monitor (ADDM) page. c) On the Automatic Database Diagnostic Monitor (ADDM) page, you should see two main findings: CPU Usage and Top SQL by DB Time. Both should be close to 100%. If they are not, ensure that what you see is the latest ADDM analysis. d) Click the “Top SQL by DB Time” link.

f) Wait on the Processing: SQL Tuning Advisor Task SQL_TUNING_… page for a while. g) You are automatically directed to the Recommendations for SQL ID:5mxdwvuf9j3vp” page from where you should see two recommendations-one for a SQL Profile and one for an index creation. h) You can investigate the consequence of implementing the recommended profile by comparing execution plans before and after profile implementation. You can do so by clicking the “Compare explain plan” eyeglass icon for the corresponding SQL Profile row. Because the potential benefit of using the proposed SQL profile is very high (see both computed Costs), you implement the SQL profile. i) On the Compare Explain Plans page, click the Recommendations for SQL ID:5mxdwvuf9j3vp locator link. j) Back to the Recommendations for SQL ID:5mxdwvuf9j3vp page, ensure that the SQL Profile row is selected, and click Implement. k) On Confirmation page, click Yes. l) On Recommendations for SQL ID:5mxdwvuf9j3vp page, you should see the following message at its top: “Confirmation: The recommended SQL Profile has been created successfully”. m) Click Return. n) On SQL Tuning Results:TASK, click the Database Instance: orcl locator link. o) Back to the Database Home Page, click the Performance tab. 5) After following the SQL Tuning Advisor recommendation to implement a SQL Profile, how can you quickly verify that the problem is solved? a) On the Performance tabbed page, you expect to see a dramatic drop for the Other wait class in the Average Active Sessions graph. However, when you view the graph you see that not has changed. 6) How do you interpret the result you see, and how would you ensure that the new profile is taken into account?



e) On the “Performance Finding Details: Top SQL by DB Time” page, click Show All Details link. You should see something similar to the following: Run SQL Tuning Advisor on the SQL statement with SQL_ID "5mxdwvuf9j3vp". Next to this recommendation, click the Run Advisor Now button.

Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) a) A profile is taken into account the next time you execute the corresponding statement. Because the SQL statement for which you created a profile takes a long time to execute, you should wait for a long time to see the benefit. To quickly see the benefit, stop and restart your workload. This executes the same SQL statements again, and the profile should be used automatically this time.

Killing stream with pid=30485 DECLARE * ERROR at line 1: ORA-00028: your session has been killed





[oracle@edrsr33p1-orcl SQL_Tuning_Advisor]$

[oracle@edrsr33p1-orcl SQL_Tuning_Advisor]$ ./start_dinas.sh Started stream with pid=31731



[oracle@edrsr33p1-orcl SQL_Tuning_Advisor]$ ./stop_dinas.sh Killing stream with pid=30486 DECLARE * ERROR at line 1: ORA-00028: your session has been killed

Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) Started stream with pid=31732 Started stream with pid=31733 Started stream with pid=31734 Started stream with pid=31735 Started stream with pid=31740 [oracle@edrsr33p1-orcl SQL_Tuning_Advisor]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/SQL_Tuning_Advisor

export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin

PIDLST=`cat /tmp/dina_pids` # # Kill all these processes # for PID in $PIDLST; do echo "Killing stream with pid=$PID" sqlplus / as sysdba @kill_dina.sql $PID >> /tmp/stop_dina.log 2>&1 sqlplus /nolog @/tmp/drop_dina.sql >> /tmp/stop_dina.log 2>&1 kill -9 $PID >> /tmp/stop_dina.log 2>&1 done -------------------------------------------------------------set set set set set

head off timing off feedback off; pagesize 0 verify off

spool /tmp/drop_dina.sql; select 'connect / as sysdba;' from dual; select 'alter system kill session ''' || sid || ',' || serial# || ''';' from v$session where process=&1; select 'exit;' from dual; spool off exit;




Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) b) Go back to the Performance tabbed page. c) On the Performance page, you should now see the benefit of the SQL Profile. There is no longer any Other waits in the Average Active Sessions graph. 7) How would you make sure that the SQL Profile was implemented? a) On the Average Active Sessions graph, click the Other wait category in the caption. b) On the Active Sessions Waiting: Other page, you should see that your statement waits for the latch free event. You can see that from the ACTIVITY(%) column. d) On the SQL Details: 5mxdwvuf9j3vp page, click the Plan Control tab in the Details section. e) You should see that this statement is associated to a SQL Profile that was manually implemented. It is part of the DEFAULT category and is ENABLED. 8) Clean up your environment by executing the following commands from your command-line window: ./stop_dians.sh ./cleanup_dina.sh [oracle@edrsr33p1-orcl SQL_Tuning_Advisor]$ ./stop_dinas.sh Killing stream with pid=31740 DECLARE * ERROR at line 1: ORA-00028: your session has been killed Killing stream with pid=31735 DECLARE * ERROR at line 1: ORA-00028: your session has been killed Killing stream with pid=31734 DECLARE * ERROR at line 1: ORA-00028: your session has been killed Killing stream with pid=31733 DECLARE * ERROR at line 1: ORA-00028: your session has been killed Killing stream with pid=31732 DECLARE * ERROR at line 1: ORA-00028: your session has been killed



c) Click the 5mxdwvuf9j3vp SQL Id link in the Top SQL table.

Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) Killing stream with pid=31731 DECLARE * ERROR at line 1: ORA-00028: your session has been killed [oracle@edrsr33p1-orcl SQL_Tuning_Advisor]$

[oracle@edrsr33p1-orcl SQL_Tuning_Advisor]$ ./cleanup_dina.sh


Session altered.



User created. old new old new




User altered.

Grant succeeded.



Revoke succeeded.

Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) Grant succeeded. ...

Grant succeeded.

Grant succeeded.

Connected. Grant succeeded. old 1: CREATE OR REPLACE DIRECTORY data_file_dir AS '&data_dir' new 1: CREATE OR REPLACE DIRECTORY data_file_dir AS '/u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/' Directory created. old new


Directory created.

Grant succeeded.

Grant succeeded.


Session altered.

Table created.

Table created.

...

Table created.




Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) Creating constraints ... Table altered.

...

Table altered.

specify path for data files as parameter 2: specify path for log files as parameter 3: specify version as parameter 4: Looking for indexes that could slow down load ... no rows selected

loading TIMES using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/time_v 3.ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/time_v 3.dat /home/oracle/time_v3.log SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:23 2008 Copyright (c) 1982, 2007, Oracle.


Save data point reached - logical record count 1000. Load completed - logical record count 1826.

loading COUNTRIES using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/coun_v 3.ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/coun_v 3.dat /home/oracle/coun_v3.log SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:24 2008 Copyright (c) 1982, 2007, Oracle.




specify password for SH as parameter 1:

Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) Load completed - logical record count 23. loading CUSTOMERS using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/cust_v 3.ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/cust1v 3.dat /home/oracle/cust1v3.log SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:24 2008

Save Save Save Save Save

data data data data data

point point point point point

reached reached reached reached reached

-

logical logical logical logical logical

All rights reserved. record record record record record

count count count count count

10000. 20000. 30000. 40000. 50000.

Load completed - logical record count 55500.

loading PRODUCTS using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/prod_v 3.ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/prod1v 3.dat /home/oracle/prod1v3.log SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:24 2008 Copyright (c) 1982, 2007, Oracle.



loading PROMOTIONS using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/prom_v 3.ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/prom1v 3.dat /home/oracle/prom1v3.log SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:25 2008 Copyright (c) 1982, 2007, Oracle.


Save data point reached - logical record count 10. Save data point reached - logical record count 20. ... Save data point reached - logical record count 500.




Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) Load completed - logical record count 503.

loading CHANNELS using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/chan_v 3.ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/chan_v 3.dat /home/oracle/chan_v3.log




loading SALES using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/sale_v 3.ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/sale1v 3.dat /home/oracle/sale1v3.log SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:25 2008 Copyright (c) 1982, 2007, Oracle.


Save data point reached - logical record count 100000. ... Save data point reached - logical record count 900000. Load completed - logical record count 916039.

loading COSTS using external table

Table created.

82112 rows created.

loading additonal SALES using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/dmsal_ v3.ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/dmsal_ v3.dat /home/oracle/dmsal_v3.log



SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:25 2008

Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:38 2008 Copyright (c) 1982, 2007, Oracle.


Save data point reached - logical record count 100. ... Save data point reached - logical record count 2800.

loading SUPPLEMENTARY DEMOGRAPHICS using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/dem_v3 .ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/dem1v3 .dat /home/oracle/dem1v3.log SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:38 2008 Copyright (c) 1982, 2007, Oracle.



Commit complete.

Enabling constraints ... Table altered.

...

Table altered.

Creating additional indexes ... Index created.

...

Index created.




Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) Create dimensions ... Dimension created.

Commit complete.


Dimension created.


no rows selected

Dimension created.


no rows selected

Dimension created.


no rows selected

Dimension created.


no rows selected Creating MVs as tables ...

View created.

Table created.



no rows selected

Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) Table created.

Index created.

Index created.

Index created. Creating materialized views ...

Materialized view created.


Creating comments ... Comment created.

...

Comment created.

Creating OLAP metadata ... <<<<< CREATE CWMLite Metadata for the Sales History Schema >>>>> <<<<< CREATE CATALOG sh_cat for Sales History >>>>> Catalog Dropped CWM Collect Garbage <<<<< CREATE the Sales CUBE >>>>> Sales amount, Sales quantity Drop SALES_CUBE prior to recreation Cube Dropped Add dimensions to SALES_CUBE and map the foreign keys Create measures for SALES_CUBE and map to columns in the fact table Set default aggregation method to SUM for all measures over TIME Add SALES_CUBE to the catalog SALES_CUBE successfully added to sh_cat



Index created.

<<<<< CREATE the Cost CUBE >>>>> Unit Cost, Unit Price < TIMES PRODUCTS CHANNELS PROMOTIONS > Drop COST_CUBE prior to recreation Cube Dropped Add dimensions to COST_CUBE and map the foreign keys Create measures for COST_CUBE and map to columns in the fact table Set default aggregation method to SUM for all measures over TIME Add COST_CUBE to the catalog COST_CUBE successfully added to sh_cat <<<<< TIME DIMENSION >>>>> Dimension - display name, description and plural name Level - display name and description Hierarchy - display name and description - default calculation hierarchy - default display hierarchy Level Attributes - name, display name, description Drop dimension attributes prior to re-creation Create dimension attributes and add their level attributes - Long Description created - Short Description created - Period Number of Days created - Period End Date created Classify entity descriptor use - Time dimension - Long description - Day name - Calendar month description - Calendar quarter description - Fiscal month description - Fiscal quarter description - Short Description - Day name - Calendar month description - Calendar quarter description - Fiscal month description - Fiscal quarter description - Time Span - Days in calendar month - Days in calendar quarter - Days in calendar year - Days in fiscal month - Days in fiscal quarter - Days in fiscal year - End Date - End of calendar month - End of calendar quarter - End of calendar year - End of fiscal month - End of fiscal quarter - End of fiscal year -



Practice 11-1: Proactively Tuning High-Load SQL Statements (continued)

<<<<< CUSTOMERS DIMENSION >>>>> Dimension - display name, description and plural name Level - display name and description Hierarchy - display name and description - default calculation hierarchy - default display hierarchy Level Attributes - name, display name, description Drop dimension attributes prior to re-creation No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop Create dimension attributes and add their level attributes - Long Description created - Short Description created - Other Customer Information created Classify entity descriptor use - Long Description - Short Description <<<<< PRODUCTS DIMENSION >>>>> Dimension - display name, description and plural name Level - display name and description Hierarchy - display name and description - default calculation hierarchy - default display hierarchy Level Attributes - name, display name, description Drop dimension attributes prior to re-creation No attribute to drop Create dimension attributes and add their level attributes - Long Description created - Short Description created Classify entity descriptor use - Long Description - Short Description <<<<< PROMOTIONS DIMENSION >>>>> Dimension - display name, description and plural name Level - display name and description Hierarchy - display name and description - default calculation hierarchy - default display hierarchy Level Attributes - name, display name, description Drop dimension attributes prior to re-creation No attribute to drop Create dimension attributes and add their level attributes - Long Description created - Short Description created




Classify entity descriptor use - Long Description - Short Description <<<<< CHANNELS DIMENSION >>>>> Dimension - display name, description and plural name Level - display name and description Hierarchy - display name and description - default calculation hierarchy - default display hierarchy Level Attributes - name, display name, description Drop dimension attributes prior to re-creation No attribute to drop Create dimension attributes and add their level attributes - Long Description created - Short Description created Classify entity descriptor use - Long Description - Short Description <<<<< FINAL PROCESSING >>>>> - Changes have been committed PL/SQL procedure successfully completed.

Commit complete.


PL/SQL procedure successfully completed. SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl SQL_Access_Advisor]$

-------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/SQL_Tuning_Advisor export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin




Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) # # Cleanup ADDM snapshot settings # sqlplus -s /NOLOG <> /tmp/cleanup_dina.log 2>&1 connect / as sysdba

rem -- change ADDM sensitiveness back to normal exec dbms_advisor.set_default_task_parameter('ADDM','DB_ACTIVITY_MIN',300 ); connect sh/sh drop index sales_time_idx; create bitmap index sales_time_bix on sales(time_id) tablespace example local nologging compute statistics;

EOF # # Cleanup sql profile # sqlplus -s /NOLOG < /tmp/cleanup_dina.log 2>&1 connect / as sysdba set set set set

head off timing off feedback off; pagesize 0

spool /tmp/drop_dyn.sql; select q'#connect / as sysdba;#' from dual; select q'#execute dbms_sqltune.drop_sql_profile('#' || name || q'#') ;#' from dba_sql_profiles ; select q'#execute dbms_advisor.delete_task('#' || task_name || q'#') ;#' from user_advisor_tasks where CREATED > SYSDATE-(1/24); select q'#connect system/oracle;#' from dual;



rem -- change INTERVAL setting to 30 minute execute dbms_workload_repository.modify_snapshot_settings(interval => 60);

Practice 11-1: Proactively Tuning High-Load SQL Statements (continued) select q'#execute dbms_advisor.delete_task('#' || task_name || q'#') ;#' from user_advisor_tasks where CREATED > SYSDATE-(1/24); spool off @/tmp/drop_dyn.sql

cp /home/oracle/solutions/SQL_Access_Advisor/sh/* $ORACLE_HOME/demo/schema/sales_history cd /home/oracle/solutions/SQL_Access_Advisor/sh sqlplus -s /NOLOG <


EOF

Practice 11-2: Using SQL Access Advisor The following scenario illustrates the types of recommendations that can be made by SQL Access Advisor. The scenario also uses the SQL Performance Analyzer to prove that recommendations made by SQL Access Advisor are good. 1) From a terminal session connected as the oracle user, execute the sqlaccessadv_setup.sh script. This script generates the necessary data that you use throughout this lab. In particular, it generates the SQL Tuning Set that is used to represent the workload you want to analyze. ./sqlaccessadv_setup.sh

SQL*Plus: Release 11.1.0.6.0 - Production on Tue Mar 18 21:14:49 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> Connected. SQL> SQL> Grant succeeded. SQL> SQL> User altered. SQL> SQL> Connected. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 PL/SQL procedure successfully completed. SQL> SQL> SQL> SQL> SQL> SQL> SQL> DROP TABLE temp_table purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> Table created. SQL> SQL> SQL> SQL> SQL> SQL> SQL> System altered. SQL> BEGIN dbms_sqltune.drop_sqlset('SQLSET_MY_SQLACCESS_WORKLOAD'); END; * ERROR at line 1:



[oracle@edrsr33p1-orcl SQL_Access_Advisor]$ ./sqlaccessadv_setup.sh

Practice 11-2: Using SQL Access Advisor (continued) ORA-13754: "SQL Tuning Set" "SQLSET_MY_SQLACCESS_WORKLOAD" does not exist for user "SH". ORA-06512: at "SYS.DBMS_SQLTUNE_INTERNAL", line 8406 ORA-06512: at "SYS.DBMS_SQLTUNE", line 2949 ORA-06512: at line 1

SQL> SQL> drop table tempjfv purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> SQL> SQL> 2 3 4 5 6 PL/SQL procedure successfully completed.

7

SQL> SQL> drop table customersjfv purge * ERROR at line 1: ORA-00942: table or view does not exist

SQL> Table created. SQL> SQL> SQL> 2 3 4 13 14 15 16 17 18 27 28 29 30 31 32 41 42 43 44 45 46 PL/SQL procedure successfully

5 6 7 19 20 21 33 34 35 47 48 49 completed.

8 22 36

9 23 37

10 24 38

SQL> SQL> SQL> COUNT(*) ---------5 1 row selected. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> PL/SQL procedure successfully completed. SQL> PL/SQL procedure successfully completed. SQL> SQL> PL/SQL procedure successfully completed. SQL> SQL> PL/SQL procedure successfully completed. SQL> SQL> LAST_ANAL --------18-MAR-08


11 25 39

12 26 40


SQL> SQL> Table created.

Practice 11-2: Using SQL Access Advisor (continued) 18-MAR-08 18-MAR-08 18-MAR-08 22-AUG-07 18-MAR-08 18-MAR-08 18-MAR-08 18-MAR-08 18-MAR-08 18-MAR-08 18-MAR-08 18-MAR-08

SQL> SQL> SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl SQL_Access_Advisor]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/SQL_Access_Advisor export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin sqlplus / as sysdba <
ECHO ON FEEDBACK 1 NUMWIDTH 10 LINESIZE 8000 TRIMSPOOL ON TAB OFF PAGESIZE 100 LONG 1000

CONNECT / AS SYSDBA grant dba to sh; alter user sh identified by sh account unlock; connect sh/sh set serveroutput on size 32768; set echo on;



14 rows selected.

Practice 11-2: Using SQL Access Advisor (continued) variable norecs number;

declare name varchar2(30); cursor name_cur1 is select task_name from user_advisor_templates where task_name like '%SQLACCESS%'; begin --------------------------------------------------------------------------- Get rid of templates, tasks and workloads. -------------------------------------------------------------------------open name_cur1; loop fetch name_cur1 into name; exit when name_cur1%NOTFOUND;

dbms_advisor.update_task_attributes(name,null,null,'FALSE','FALSE'); dbms_advisor.delete_task(name); end loop; close name_cur1; end; /

Rem make a temp table

DROP TABLE temp_table purge; CREATE TABLE temp_table AS SELECT * FROM SYS.WRI\$_ADV_SQLW_STMTS WHERE NULL IS NOT NULL;

Rem create a large number of pseudo-random (repeatable) queries in the temporary table

alter system flush shared_pool; execute dbms_sqltune.drop_sqlset('SQLSET_MY_SQLACCESS_WORKLOAD'); drop table tempjfv purge; create table tempjfv (c number, d varchar2(1000));



Rem Clean up

Practice 11-2: Using SQL Access Advisor (continued)

drop table customersjfv purge; create table customersjfv as select * from customers;

DECLARE sql_stmt varchar2(2000); sqlsetname VARCHAR2(30); sqlsetcur dbms_sqltune.sqlset_cursor; refid NUMBER; k NUMBER := 0; num_queries NUMBER := 500; BEGIN sql_stmt := 'SELECT /* QueryJFV 2 */ ch.channel_class, c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold) sales_amount FROM sh.sales s, sh.times t, sh.customers c, sh.channels ch WHERE s.time_id = t.time_id AND s.cust_id = c.cust_id AND s.channel_id = ch.channel_id AND c.cust_state_province = ''CA'' AND ch.channel_desc in (''Internet'',''Catalog'') AND t.calendar_quarter_desc IN (''1999-01'',''1999-02'') GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc'; insert into temp_table values(1,1,NULL,0,'SH','Access Advisor','Workload',0,0,0,0,1,100,2,to_date('02-FEB2007'),3,0,sql_stmt,1); sql_stmt := 'SELECT /* QueryJFV 3 */ ch.channel_class, c.cust_city, t.calendar_quarter_desc, SUM(s.amount_sold) sales_amount FROM sh.sales s, sh.times t, sh.customers c, sh.channels ch WHERE s.time_id = t.time_id AND s.cust_id = c.cust_id AND s.channel_id = ch.channel_id AND c.cust_state_province = ''CA'' AND ch.channel_desc in (''Internet'',''Catalog'') AND t.calendar_quarter_desc IN (''1999-03'',''1999-04'') GROUP BY ch.channel_class, c.cust_city, t.calendar_quarter_desc'; insert into temp_table values(1,1,NULL,0,'SH','Access Advisor','Workload',0,0,0,0,1,100,2,to_date('02-FEB2007'),3,0,sql_stmt,1);



begin for i in 1..20000 loop insert into tempjfv values(i,'aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa'); end loop; commit; end; /

Practice 11-2: Using SQL Access Advisor (continued) sql_stmt := 'SELECT /* QueryJFV 4 */ c.country_id, c.cust_city, c.cust_last_name FROM sh.customers c WHERE c.country_id in (52790, 52798) ORDER BY c.country_id, c.cust_city, c.cust_last_name'; insert into temp_table values(1,1,NULL,0,'SH','Access Advisor','Workload',0,0,0,0,1,100,2,to_date('02-FEB2007'),3,0,sql_stmt,1);

sql_stmt := 'select /* func_indx */ count(*) from tempjfv where abs(c)=5';

sql_stmt := 'SELECT /* QueryJFV 5 */ * FROM sh.customersjfv WHERE cust_state_province = ''CA'''; insert into temp_table values(1,1,NULL,0,'SH','Access Advisor','Workload',0,0,0,0,1,100,2,to_date('02-FEB2007'),3,0,sql_stmt,1);

sqlsetname := 'SQLSET_MY_SQLACCESS_WORKLOAD'; dbms_sqltune.create_sqlset(sqlsetname, 'Generated STS'); OPEN sqlsetcur FOR SELECT SQLSET_ROW(null,null, sql_text, null, null, username, module, action, elapsed_time, cpu_time, buffer_gets, disk_reads, 0,rows_processed, 0, executions, 0, optimizer_cost, null, priority, command_type, to_char(last_execution_date,'yyyy-mmdd/hh24:mi:ss'), 0,0,NULL,0,NULL,NULL ) FROM temp_table; dbms_sqltune.load_sqlset(sqlsetname, sqlsetcur); END; /

SELECT COUNT(*) FROM TABLE(DBMS_SQLTUNE.SELECT_SQLSET('SQLSET_MY_SQLACCESS_WORKLOAD'));

Rem Cleanup anything left behind



insert into temp_table values(1,1,NULL,0,'SH','Access Advisor','Workload',0,0,0,0,1,100,2,to_date('02-FEB2007'),3,0,sql_stmt,1);

Practice 11-2: Using SQL Access Advisor (continued) execute dbms_advisor.delete_task('%'); execute dbms_advisor.delete_sqlwkld('%'); EXECUTE DBMS_STATS.UNLOCK_SCHEMA_STATS('SH'); execute dbms_stats.gather_schema_stats(ownname => 'SH', estimate_percent=> DBMS_STATS.AUTO_SAMPLE_SIZE, method_opt => 'FOR ALL COLUMNS SIZE AUTO', degree => 4 ); select distinct last_analyzed from dba_tab_statistics where owner='SH'; REM EXECUTE DBMS_STATS.LOCK_SCHEMA_STATS('SH');

FIN!

2) Using Enterprise Manager, create a SQL Access Advisor tuning task based on the captured workload held in the SH.SQLSET_MY_ACCESS_WORKLOAD SQL tuning set using the SQLACCESS_WAREHOUSE template. a) Connect to Enterprise Manager Database Control as the sh user (password: sh). On the Home page, click the Advisor Central link in the Related Links section. b) On the Advisor Central page, click the SQL Advisors link. Then on the SQL Advisors page, click the SQL Access Advisor link. c) On the Initial Options page, select Inherit Options from a previously saved Task or Template, and then select the SQLACCESS_WAREHOUSE template. After this is done, click Continue. d) On the Workload Source page, select Use an existing SQL Tuning Set and enter SH.SQLSET_MY_SQLACCESS_WORKLOAD in the SQL Tuning Set field. (This SQL Tuning Set was generated earlier. It represents a warehouse workload that you want to analyze.) Click Next. e) On the Recommendation Options page, ensure that all possible access structures are selected, and that Comprehensive is selected. After this is done, click Next. f) On the Schedule page, enter MY_SQLACCESS_TASK in the Task Name field. Select the first Time Zone from the provided list (Click the torch icon.). After this is done, click Next. g) On the Review page, click Submit. h) Back to the Advisor Central page, click Refresh until the Status of your task is COMPLETED. i) After this is done, click the MY_SQLACCESS_TASK link in the Results table. 3) After this is done, investigate the proposed recommendations: a) Back to the Advisor Central page, click the MY_SQLACCESS_TASK link in the Results table. The task should have COMPLETED as the status.



exit;

Practice 11-2: Using SQL Access Advisor (continued) b) This takes you to the Results page. From this page, you can see the potential benefit of implementing the SQL Access Advisor recommendations on the workload. There should be a huge difference between the original and the new costs. Click the Recommendation subtab.

d) Ensure that all recommendations are selected, and click the Recommendation Details button. This takes you to the Details page, where you can see more details about each of the recommendations, as well as the corresponding SQL statements from the workload that are affected by these recommendations. You should see the following recommendations: - Partition CUSTOMERS table. - Create four materialized view log. - Create a materialized view. - Create one bitmap index. - Create a function-based index. - Create a B*-tree index on multiple columns. e) Click OK. 4) Try to implement the generated recommendations. What happens, and why? a) Back to the Recommendations subtab, click the Schedule Implementation button. b) On the Schedule Implementation page, a warning is displayed indicating that the wizard will not try to implement its recommendations because some of them are very important changes that should be looked at closely by the administrator. c) Click the Show SQL button to look at the script you could use to implement all recommendations. In fact, you already created this script and you will use it later in this lab. After you review the script, click Done. d) Back to the Schedule Implementation page, click Cancel. e) Click the Advisor Central locator link at the top of the “Results for Task” page. f) On the Advisor Central page, select the SQL Access Advisor MY_SQLACCESS_TASK task and click Delete. g) On the Information page, click Yes. 5) Use Enterprise Manager to verify the performance improvement if you implement the recommendations mentioned. a) Click the Database tab at the top-right corner and then the “Software and Support” tab. On the “Software and Support” tabbed page, click the SQL Performance Analyzer link. You want to prove that implementing the recommendations is beneficial. b) On the SQL Performance Analyzer page, click the Guided Workflow link.



c) On the Recommendations subtab, you can see the high-level overview of the recommendations. Basically, all possible types of recommendations were generated for this workload (Indexes, Materialized Views, Materialized View Logs, Partitions, and Others).

Practice 11-2: Using SQL Access Advisor (continued) c) On the Guided Workflow page, click the Execute icon on the line corresponding to step 1. d) On the Create SQL Performance Analyzer Task page, enter MY_SPA_TASK in the SQL Performance Analyzer Task Name field. Then, enter SH.SQLSET_MY_SQLACCESS_WORKLOAD in the SQL Tuning Set Name field. After this is done, click Create. e) Back to the Guided Workflow page, click the Execute icon for step 2.

g) Wait on the Guided Workflow page until step 2 is completed. h) From your terminal session, connect as the sh user (password: sh) in the SQL*Plus session, and execute the implement.sql script. This script is a precreated script corresponding to the recommendations previously generated by your SQL Access Advisor session. cd /home/oracle/solutions/SQL_Access_Advisor [oracle@edrsr33p1-orcl SQL_Access_Advisor]$ ls implement.sql revert.sh sqlaccessadv_setup.sh [oracle@edrsr33p1-orcl SQL_Access_Advisor]$ sqlplus sh/sh SQL*Plus: Release 11.1.0.6.0 - Production on Tue Mar 18 21:57:25 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5 6 7 8 9 10 11 12 13

@implement Rem Rem Creating new partitioned table Rem CREATE TABLE "SH"."CUSTOMERS1" ( "CUST_ID" NUMBER, "CUST_FIRST_NAME" VARCHAR2(20), "CUST_LAST_NAME" VARCHAR2(40), "CUST_GENDER" CHAR(1), "CUST_YEAR_OF_BIRTH" NUMBER(4,0), "CUST_MARITAL_STATUS" VARCHAR2(20), "CUST_STREET_ADDRESS" VARCHAR2(40), "CUST_POSTAL_CODE" VARCHAR2(10), "CUST_CITY" VARCHAR2(30), "CUST_CITY_ID" NUMBER, "CUST_STATE_PROVINCE" VARCHAR2(40), "CUST_STATE_PROVINCE_ID" NUMBER,



f) On the Create Replay Trial page, enter MY_SQL_REPLAY_BEFORE in the Replay Trial Name field, and ensure that you select the Trial environment established check box. Then, click Submit.

14 "COUNTRY_ID" NUMBER, 15 "CUST_MAIN_PHONE_NUMBER" VARCHAR2(25), 16 "CUST_INCOME_LEVEL" VARCHAR2(30), 17 "CUST_CREDIT_LIMIT" NUMBER, 18 "CUST_EMAIL" VARCHAR2(30), 19 "CUST_TOTAL" VARCHAR2(14), 20 "CUST_TOTAL_ID" NUMBER, 21 "CUST_SRC_ID" NUMBER, 22 "CUST_EFF_FROM" DATE, 23 "CUST_EFF_TO" DATE, 24 "CUST_VALID" VARCHAR2(1) 25 ) PCTFREE 10 PCTUSED 40 INITRANS 1 MAXTRANS 255 NOCOMPRESS NOLOGGING 26 TABLESPACE "EXAMPLE" 27 PARTITION BY RANGE ("CUST_ID") INTERVAL( 3000) ( PARTITION VALUES LESS THAN (3000) 28 ); Table created. SQL> SQL> SQL> SQL> SQL>

Rem Rem Copying comments to new partitioned table Rem COMMENT ON COLUMN "SH"."CUSTOMERS1"."CUST_ID" IS 'primary key';

Comment created. SQL> SQL> COMMENT ON COLUMN "SH"."CUSTOMERS1"."CUST_FIRST_NAME" IS 'first name of the customer'; Comment created. SQL> SQL> COMMENT ON COLUMN "SH"."CUSTOMERS1"."CUST_LAST_NAME" IS 'last name of the customer'; Comment created. SQL> SQL> COMMENT ON COLUMN "SH"."CUSTOMERS1"."CUST_GENDER" IS 'gender; low cardinality attribute'; Comment created. SQL> SQL> COMMENT ON COLUMN "SH"."CUSTOMERS1"."CUST_YEAR_OF_BIRTH" IS 'customer year of birth'; Comment created. SQL> SQL> COMMENT ON COLUMN "SH"."CUSTOMERS1"."CUST_MARITAL_STATUS" IS 'customer marital status; low cardinality attribute'; Comment created.




Practice 11-2: Using SQL Access Advisor (continued) SQL> SQL> COMMENT ON COLUMN "SH"."CUSTOMERS1"."CUST_STREET_ADDRESS" IS 'customer street address'; Comment created. SQL> SQL> COMMENT ON COLUMN "SH"."CUSTOMERS1"."CUST_POSTAL_CODE" IS 'postal code of the customer';

SQL> SQL> SQL> COMMENT ON COLUMN "SH"."CUSTOMERS1"."CUST_CITY" IS 'city where the customer lives'; Comment created. SQL> SQL> COMMENT ON COLUMN "SH"."CUSTOMERS1"."CUST_STATE_PROVINCE" IS 'customer geography: state or province'; Comment created. SQL> SQL> COMMENT ON COLUMN "SH"."CUSTOMERS1"."COUNTRY_ID" IS 'foreign key to the countries table (snowflake)'; Comment created. SQL> SQL> COMMENT ON COLUMN "SH"."CUSTOMERS1"."CUST_MAIN_PHONE_NUMBER" IS 'customer main phone number'; Comment created. SQL> SQL> COMMENT ON COLUMN "SH"."CUSTOMERS1"."CUST_INCOME_LEVEL" IS 'customer income level'; Comment created. SQL> SQL> COMMENT ON COLUMN "SH"."CUSTOMERS1"."CUST_CREDIT_LIMIT" IS 'customer credit limit'; Comment created. SQL> SQL> COMMENT ON COLUMN "SH"."CUSTOMERS1"."CUST_EMAIL" IS 'customer email id'; Comment created. SQL>



Comment created.

Practice 11-2: Using SQL Access Advisor (continued) SQL> COMMENT ON TABLE "SH"."CUSTOMERS1" IS 'dimension table'; Comment created. SQL> SQL> Rem SQL> Rem Copying constraints to new partitioned table SQL> Rem SQL> ALTER TABLE "SH"."CUSTOMERS1" ADD CONSTRAINT "CUSTOMERS_PK1" PRIMARY KEY ("CUST_ID") 2 USING INDEX PCTFREE 10 INITRANS 2 MAXTRANS 255 NOLOGGING COMPUTE STATISTICS 3 TABLESPACE "EXAMPLE" ENABLE NOVALIDATE;

SQL> SQL> Rem SQL> Rem Copying referential constraints to new partitioned table SQL> Rem SQL> ALTER TABLE "SH"."CUSTOMERS1" ADD CONSTRAINT "CUSTOMERS_COUNTRY_FK1" FOREIGN KEY ("COUNTRY_ID") 2 REFERENCES "SH"."COUNTRIES" ("COUNTRY_ID") ENABLE NOVALIDATE; Table altered. SQL> SQL> Rem SQL> Rem Copying indexes to new partitioned table SQL> Rem SQL> CREATE BITMAP INDEX "SH"."CUSTOMERS_GENDER_BIX1" ON "SH"."CUSTOMERS1" ("CUST_GENDER") 2 PCTFREE 10 INITRANS 2 MAXTRANS 255 NOLOGGING COMPUTE STATISTICS 3 TABLESPACE "EXAMPLE" LOCAL; Index created. SQL> SQL> SQL> SQL> SQL>

Rem Rem Copying object grants to new partitioned table Rem GRANT SELECT ON "SH"."CUSTOMERS1" TO "BI";

Grant succeeded. SQL> SQL> Rem SQL> Rem Populating new partitioned table with data from original table SQL> Rem SQL> INSERT /*+ APPEND */ INTO "SH"."CUSTOMERS1" 2 SELECT * FROM "SH"."CUSTOMERS"; 55500 rows created. SQL> COMMIT;



Table altered.

Practice 11-2: Using SQL Access Advisor (continued) Commit complete. SQL> SQL> begin 2 dbms_stats.gather_table_stats('"SH"', '"CUSTOMERS1"', NULL, dbms_stats.auto_sample_size); 3 end; 4 /

SQL> SQL> Rem SQL> Rem Renaming tables to give new partitioned table the original table name SQL> Rem SQL> ALTER TABLE "SH"."CUSTOMERS" RENAME TO "CUSTOMERS11"; Table altered. SQL> ALTER TABLE "SH"."CUSTOMERS1" RENAME TO "CUSTOMERS"; Table altered. SQL> SQL> SQL> SQL> SQL>

Rem Rem Revalidating dimensions for use with new partitioned table Rem ALTER DIMENSION "SH"."CUSTOMERS_DIM" COMPILE;

Dimension altered. SQL> SQL> SQL> CREATE MATERIALIZED VIEW LOG ON 2 "SH"."CUSTOMERS" 3 WITH ROWID, SEQUENCE("CUST_ID","CUST_CITY","CUST_STATE_PROVINCE") 4 INCLUDING NEW VALUES; Materialized view log created. SQL> SQL> CREATE MATERIALIZED VIEW LOG ON 2 "SH"."CHANNELS" 3 WITH ROWID, SEQUENCE("CHANNEL_ID","CHANNEL_DESC","CHANNEL_CLASS") 4 INCLUDING NEW VALUES; Materialized view log created. SQL> SQL> 2 3 4

CREATE MATERIALIZED VIEW LOG ON "SH"."TIMES" WITH ROWID, SEQUENCE("TIME_ID","CALENDAR_QUARTER_DESC") INCLUDING NEW VALUES;




Practice 11-2: Using SQL Access Advisor (continued) Materialized view log created. SQL> SQL> CREATE MATERIALIZED VIEW LOG ON 2 "SH"."SALES" 3 WITH ROWID, SEQUENCE("CUST_ID","TIME_ID","CHANNEL_ID","AMOUNT_SOLD") 4 INCLUDING NEW VALUES;

SQL> SQL> CREATE MATERIALIZED VIEW "SH"."MV_01DF0000" 2 REFRESH FAST WITH ROWID 3 ENABLE QUERY REWRITE 4 AS SELECT SH.CUSTOMERS.CUST_STATE_PROVINCE C1, SH.CUSTOMERS.CUST_CITY C2, SH.CHANNELS.CHANNEL_CLASS 5 C3, SH.CHANNELS.CHANNEL_DESC C4, SH.TIMES.CALENDAR_QUARTER_DESC C5, SUM("SH"."SALES"."AMOUNT_SOLD") 6 M1, COUNT("SH"."SALES"."AMOUNT_SOLD") M2, COUNT(*) M3 FROM SH.CUSTOMERS, 7 SH.CHANNELS, SH.TIMES, SH.SALES WHERE SH.SALES.CHANNEL_ID = SH.CHANNELS.CHANNEL_ID 8 AND SH.SALES.TIME_ID = SH.TIMES.TIME_ID AND SH.SALES.CUST_ID = SH.CUSTOMERS.CUST_ID 9 AND (SH.TIMES.CALENDAR_QUARTER_DESC IN ('1999-04', '1999-03', '1999-02' 10 , '1999-01')) AND (SH.CHANNELS.CHANNEL_DESC IN ('Internet', 'Catalog' 11 )) AND (SH.CUSTOMERS.CUST_STATE_PROVINCE = 'CA') GROUP BY SH.CUSTOMERS.CUST_STATE_PROVINCE, 12 SH.CUSTOMERS.CUST_CITY, SH.CHANNELS.CHANNEL_CLASS, SH.CHANNELS.CHANNEL_DESC, 13 SH.TIMES.CALENDAR_QUARTER_DESC; Materialized view created. SQL> SQL> begin 2 dbms_stats.gather_table_stats('"SH"','"MV_01DF0000"',NULL,dbms_stats .auto_sample_size); 3 end; 4 / PL/SQL procedure successfully completed. SQL> SQL> 2 3 4

CREATE BITMAP INDEX "SH"."CUSTOMERSJFV_IDX_01DF0000" ON "SH"."CUSTOMERSJFV" ("CUST_STATE_PROVINCE") COMPUTE STATISTICS;

Index created. SQL>



Materialized view log created.

Practice 11-2: Using SQL Access Advisor (continued) SQL> 2 3 4

CREATE INDEX "SH"."TEMPJFV_IDX_01DF0001" ON "SH"."TEMPJFV" (ABS("C")) COMPUTE STATISTICS;

Index created. SQL> SQL> 2 3 4

CREATE INDEX "SH"."CUSTOMERS_IDX_01DF0002" ON "SH"."CUSTOMERS" ("COUNTRY_ID","CUST_CITY","CUST_LAST_NAME") COMPUTE STATISTICS;

SQL> SQL> exit Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl SQL_Access_Advisor]$

i) Back to your Guided Workflow page, click the Execute icon corresponding to step 3. j) On the Create Replay Trial page, enter MY_SQL_REPLAY_AFTER in the Replay Trial Name field. Ensure that you select the Trial environment established check box, and click Submit. k) Wait until step 3 is completed. l) Back to your Guided Workflow Enterprise Manager page, click the Execute icon corresponding to step 4. m) On the Run Replay Trial Comparison page, ensure that you create a comparison between MY_SQL_REPLAY_BEFORE and MY_SQL_REPLAY_AFTER. Click Submit. n) Wait until step 4 is completed. o) Back to your Guided Workflow Enterprise Manager page, click the Execute icon corresponding to step 5. p) On the SQL Performance Analyzer Task Result page, you can clearly see that the second trial is much faster than the original one. You should see that all five SQL statements are improved in the second trial due a changed execution plan. q) To get more details, analyze the differences in execution plan for all five statements. You can do so directly from the SQL Performance Analyzer Task Result page by clicking each SQL ID in the Top 10 table. Each time you click a SQL ID, you can see in the SQL Details section all statistics differences between the two trials as well as the differences in execution plans.



Index created.

Practice 11-2: Using SQL Access Advisor (continued) r) After this is done, go back to the SQL Performance Analyzer page (Home > Software and Support > SQL Performance Analyzer), and delete MY_SPA_TASK by selecting it and clicking Delete. On the Confirmation page, click Delete. s) Log out from Enterprise Manager. 6) From a terminal session, execute the revert.sh script to return to the situation you were in before you started the lab. [oracle@edrsr33p1-orcl SQL_Access_Advisor]$ ./revert.sh



Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> Connected. SQL> SQL> Grant succeeded. SQL> SQL> User altered. SQL> SQL> Connected. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 PL/SQL procedure successfully completed. SQL> SQL> SQL> SQL> SQL> SQL> Table dropped. SQL> SQL> System altered. SQL> SQL> Table dropped. SQL> SQL> Table dropped. SQL> SQL> SQL> PL/SQL procedure successfully completed. SQL> PL/SQL procedure successfully completed. SQL> SQL> PL/SQL procedure successfully completed.



SQL*Plus: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:02 2008

Practice 11-2: Using SQL Access Advisor (continued) SQL> SQL> SQL> PL/SQL procedure successfully completed. SQL> SQL> SQL> SQL> Materialized view log dropped. SQL> SQL> Materialized view log dropped. SQL> SQL> Materialized view log dropped.

SQL> SQL> Materialized view dropped. SQL> SQL> Index dropped. SQL> SQL> Table dropped. SQL> SQL> Table dropped. SQL> SQL> Connected. SQL> SQL> Revoke succeeded. SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> ... SQL> SQL> SQL>

SQL> SQL> Rem Rem $Header: sh_main.sql 06-mar-2008.15:00:45 cbauwens Exp $ Rem Rem sh_main.sql Rem Rem Copyright (c) 2001, 2008, Oracle. All rights reserved. Rem Rem NAME Rem sh_main.sql - Main schema creation and load script Rem SET ECHO OFF

specify password for SH as parameter 1: specify default tablespace for SH as parameter 2: specify temporary tablespace for SH as parameter 3: specify password for SYS as parameter 4: specify directory path for the data files as parameter 5: writeable directory path for the log files as parameter 6:



SQL> SQL> Materialized view log dropped.

Practice 11-2: Using SQL Access Advisor (continued) specify version as parameter 7:

Session altered.



old new old new




User altered.

Grant succeeded.

Grant succeeded.

...

Grant succeeded.

Grant succeeded.

PL/SQL procedure successfully completed. Connected. Grant succeeded. old 1: CREATE OR REPLACE DIRECTORY data_file_dir AS '&data_dir' new 1: CREATE OR REPLACE DIRECTORY data_file_dir AS '/u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/' Directory created. old new




User created.

Practice 11-2: Using SQL Access Advisor (continued) Directory created. Grant succeeded.

Grant succeeded.

Grant succeeded. Connected.

Session altered.

Table created.

Table created.

...

Table created.

Creating constraints ... Table altered.

...

Table altered.

specify password for SH as parameter 1: specify path for data files as parameter 2: specify path for log files as parameter 3: specify version as parameter 4: Looking for indexes that could slow down load ... no rows selected

loading TIMES using:



Session altered.

Practice 11-2: Using SQL Access Advisor (continued) /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/time_v 3.ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/time_v 3.dat /home/oracle/time_v3.log SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:23 2008 Copyright (c) 1982, 2007, Oracle.


Save data point reached - logical record count 1000.

loading COUNTRIES using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/coun_v 3.ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/coun_v 3.dat /home/oracle/coun_v3.log SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:24 2008 Copyright (c) 1982, 2007, Oracle.



loading CUSTOMERS using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/cust_v 3.ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/cust1v 3.dat /home/oracle/cust1v3.log SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:24 2008 Copyright (c) 1982, 2007, Oracle. Save Save Save Save Save

data data data data data

point point point point point

reached reached reached reached reached

-

logical logical logical logical logical

All rights reserved. record record record record record

count count count count count

10000. 20000. 30000. 40000. 50000.


loading PRODUCTS using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/prod_v 3.ctl




Practice 11-2: Using SQL Access Advisor (continued) /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/prod1v 3.dat /home/oracle/prod1v3.log SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:24 2008 Copyright (c) 1982, 2007, Oracle.


loading PROMOTIONS using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/prom_v 3.ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/prom1v 3.dat /home/oracle/prom1v3.log SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:25 2008 Copyright (c) 1982, 2007, Oracle.


Save data point reached - logical record count 10. Save data point reached - logical record count 20. ... Save data point reached - logical record count 500. Load completed - logical record count 503.

loading CHANNELS using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/chan_v 3.ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/chan_v 3.dat /home/oracle/chan_v3.log SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:25 2008 Copyright (c) 1982, 2007, Oracle.



loading SALES using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/sale_v 3.ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/sale1v 3.dat /home/oracle/sale1v3.log




Practice 11-2: Using SQL Access Advisor (continued) SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:25 2008 Copyright (c) 1982, 2007, Oracle.



Table created.

82112 rows created.

loading additonal SALES using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/dmsal_ v3.ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/dmsal_ v3.dat /home/oracle/dmsal_v3.log SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:38 2008 Copyright (c) 1982, 2007, Oracle.



loading SUPPLEMENTARY DEMOGRAPHICS using: /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/dem_v3 .ctl /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/dem1v3 .dat /home/oracle/dem1v3.log SQL*Loader: Release 11.1.0.6.0 - Production on Thu Mar 20 15:22:38 2008 Copyright (c) 1982, 2007, Oracle.





loading COSTS using external table

Practice 11-2: Using SQL Access Advisor (continued) Commit complete.

Enabling constraints ... Table altered.

...

Creating additional indexes ... Index created.

...

Index created.

Create dimensions ... Dimension created.

Commit complete.


no rows selected

Dimension created.


no rows selected

Dimension created.


no rows selected



Table altered.

Practice 11-2: Using SQL Access Advisor (continued) Dimension created.


no rows selected

Dimension created.

no rows selected Creating MVs as tables ...

View created.

Table created.

Table created.

Index created.

Index created.

Index created.

Index created. Creating materialized views ...



Creating comments ... Comment created.

...





Creating OLAP metadata ... <<<<< CREATE CWMLite Metadata for the Sales History Schema >>>>> <<<<< CREATE CATALOG sh_cat for Sales History >>>>> Catalog Dropped CWM Collect Garbage <<<<< CREATE the Sales CUBE >>>>> Sales amount, Sales quantity Drop SALES_CUBE prior to recreation Cube Dropped Add dimensions to SALES_CUBE and map the foreign keys Create measures for SALES_CUBE and map to columns in the fact table Set default aggregation method to SUM for all measures over TIME Add SALES_CUBE to the catalog SALES_CUBE successfully added to sh_cat <<<<< CREATE the Cost CUBE >>>>> Unit Cost, Unit Price < TIMES PRODUCTS CHANNELS PROMOTIONS > Drop COST_CUBE prior to recreation Cube Dropped Add dimensions to COST_CUBE and map the foreign keys Create measures for COST_CUBE and map to columns in the fact table Set default aggregation method to SUM for all measures over TIME Add COST_CUBE to the catalog COST_CUBE successfully added to sh_cat <<<<< TIME DIMENSION >>>>> Dimension - display name, description and plural name Level - display name and description Hierarchy - display name and description - default calculation hierarchy - default display hierarchy Level Attributes - name, display name, description Drop dimension attributes prior to re-creation Create dimension attributes and add their level attributes - Long Description created - Short Description created - Period Number of Days created - Period End Date created Classify entity descriptor use - Time dimension - Long description - Day name - Calendar month description



Comment created.

-

Calendar quarter description Fiscal month description Fiscal quarter description Short Description Day name Calendar month description Calendar quarter description Fiscal month description Fiscal quarter description Time Span Days in calendar month Days in calendar quarter Days in calendar year Days in fiscal month Days in fiscal quarter Days in fiscal year End Date End of calendar month End of calendar quarter End of calendar year End of fiscal month End of fiscal quarter End of fiscal year

<<<<< CUSTOMERS DIMENSION >>>>> Dimension - display name, description and plural name Level - display name and description Hierarchy - display name and description - default calculation hierarchy - default display hierarchy Level Attributes - name, display name, description Drop dimension attributes prior to re-creation No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop No attribute to drop Create dimension attributes and add their level attributes - Long Description created - Short Description created - Other Customer Information created Classify entity descriptor use - Long Description - Short Description <<<<< PRODUCTS DIMENSION >>>>> Dimension - display name, description and plural name Level - display name and description Hierarchy - display name and description - default calculation hierarchy




- default display hierarchy Level Attributes - name, display name, description Drop dimension attributes prior to re-creation No attribute to drop Create dimension attributes and add their level attributes - Long Description created - Short Description created Classify entity descriptor use - Long Description - Short Description <<<<< PROMOTIONS DIMENSION >>>>> Dimension - display name, description and plural name Level - display name and description Hierarchy - display name and description - default calculation hierarchy - default display hierarchy Level Attributes - name, display name, description Drop dimension attributes prior to re-creation No attribute to drop Create dimension attributes and add their level attributes - Long Description created - Short Description created Classify entity descriptor use - Long Description - Short Description <<<<< CHANNELS DIMENSION >>>>> Dimension - display name, description and plural name Level - display name and description Hierarchy - display name and description - default calculation hierarchy - default display hierarchy Level Attributes - name, display name, description Drop dimension attributes prior to re-creation No attribute to drop Create dimension attributes and add their level attributes - Long Description created - Short Description created Classify entity descriptor use - Long Description - Short Description <<<<< FINAL PROCESSING >>>>> - Changes have been committed PL/SQL procedure successfully completed.

Commit complete.





Practice 11-2: Using SQL Access Advisor (continued) PL/SQL procedure successfully completed. SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl SQL_Access_Advisor]$

-------------------------------------------------------------#!/bin/bash

export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin:/bin cp * $ORACLE_HOME/demo/schema/sales_history sqlplus / as sysdba <
ECHO ON FEEDBACK 1 NUMWIDTH 10 LINESIZE 8000 TRIMSPOOL ON TAB OFF PAGESIZE 100 LONG 1000

CONNECT / AS SYSDBA grant dba to sh; alter user sh identified by sh account unlock; connect sh/sh set serveroutput on size 32768; set echo on; variable norecs number;

Rem Clean up

declare name varchar2(30); cursor name_cur1 is select task_name from user_advisor_templates where task_name like '%SQLACCESS%';



cd /home/oracle/solutions/SQL_Access_Advisor/sh

Practice 11-2: Using SQL Access Advisor (continued) begin --------------------------------------------------------------------------- Get rid of templates, tasks and workloads. -------------------------------------------------------------------------open name_cur1;

dbms_advisor.update_task_attributes(name,null,null,'FALSE','FALSE'); dbms_advisor.delete_task(name); end loop; close name_cur1; end; /

Rem make a temp table

DROP TABLE temp_table purge; alter system flush shared_pool; drop table tempjfv purge; drop table customersjfv purge;

execute dbms_advisor.delete_task('%'); execute dbms_advisor.delete_sqlwkld('%'); execute dbms_sqltune.drop_sqlset('SQLSET_MY_SQLACCESS_WORKLOAD');

EXECUTE DBMS_STATS.UNLOCK_SCHEMA_STATS('SH');

DROP MATERIALIZED VIEW LOG ON "SH"."CUSTOMERS"; DROP MATERIALIZED VIEW LOG ON "SH"."CHANNELS"; DROP MATERIALIZED VIEW LOG ON "SH"."TIMES"; DROP MATERIALIZED VIEW LOG ON "SH"."SALES"; DROP MATERIALIZED VIEW "SH"."MV_01DF0000"; DROP INDEX "SH"."CUSTOMERS_IDX_01DF0002";



loop fetch name_cur1 into name; exit when name_cur1%NOTFOUND;

Practice 11-2: Using SQL Access Advisor (continued) DROP TABLE "SH"."CUSTOMERS" PURGE; DROP TABLE "SH"."CUSTOMERS11" CASCADE CONSTRAINTS PURGE; connect / as sysdba revoke dba from sh; @sh_main sh example temp oracle /u01/app/oracle/product/11.1.0/db_1/demo/schema/sales_history/ /home/oracle/ v3 exit;


FIN!


Practice 11-3: Using Automatic SQL Tuning In this practice, you manually launch Automatic SQL Tuning to automatically tune a small application workload. You then investigate the outcomes and configuration possibilities.


1) On the Server page, click Automated Maintenance Tasks, check that Status is set to Enabled, and click Configure. Click the Configure button next to Automatic SQL Tuning. Select Yes for “Automatic Implementation of SQL Profiles.” Then, click Apply. Execute the ast_setup.sh script from a terminal window connected as the oracle user. This script creates the AST user used throughout this practice, turns off automatic maintenance tasks, and drops any existing profiles on queries executed by the AST user. $ cd /home/oracle/solutions/Automatic_SQL_Tuning $ ./ast_setup.sh [oracle@edrsr33p1-orcl Automatic_SQL_Tuning]$ ./ast_setup.sh SQL*Plus: Release 11.1.0.6.0 - Production on Tue Mar 18 15:31:49 2008 Copyright (c) 1982, 2007, Oracle.


Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> SQL> SQL> drop user ast cascade * ERROR at line 1: ORA-01918: user 'AST' does not exist

SQL> SQL> User created. SQL> SQL> Grant succeeded. SQL> SQL> System altered. SQL> SQL> SQL> SQL> SQL> SQL> System altered. SQL> SQL> SQL> SQL> SQL> SQL> PL/SQL procedure successfully completed. SQL> SQL> SQL> SQL> SQL> SQL> 2 3 PL/SQL procedure successfully completed.

4

5

6


7

8

9

Practice 11-3: Using Automatic SQL Tuning (continued) SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Automatic_SQL_Tuning]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Automatic_SQL_Tuning

export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin sqlplus / as sysdba <



Practice 11-3: Using Automatic SQL Tuning (continued) / FIN!

2) In preparation for the practice, you should execute a workload. Execute the run_workload_stream.sh script. This script executes, multiple times, a query that is not correctly optimized. The query in question uses hints that force the optimizer to pick a suboptimal execution plan. The script execute for approximately 30 seconds. ./run_workload_stream.sh



Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> SQL> SQL> no rows selected SQL> no rows selected SQL> no rows selected ... SQL> no rows selected SQL> no rows selected SQL> no rows selected SQL> no rows selected SQL> no rows selected SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining



[oracle@edrsr33p1-orcl Automatic_SQL_Tuning]$ ./run_workload_stream.sh Tue Mar 18 15:38:05 GMT-7 2008

Practice 11-3: Using Automatic SQL Tuning (continued) and Real Application Testing options Tue Mar 18 15:38:23 GMT-7 2008 [oracle@edrsr33p1-orcl Automatic_SQL_Tuning]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Automatic_SQL_Tuning export ORACLE_SID=orcl

export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin date sqlplus ast/ast <
3) Automatic SQL Tuning is implemented using an automated task that runs during maintenance windows. However, you do not wait for the next maintenance window to open. Instead, you force the opening of your next maintenance window now. This automatically triggers the Automatic SQL Tuning task. Execute the run_ast.sh script to open your next maintenance window now. The script’s execution takes a couple of minutes. ./run_ast.sh [oracle@edrsr33p1-orcl Automatic_SQL_Tuning]$ ./run_ast.sh Tue Mar 18 15:43:48 GMT-7 2008 SQL*Plus: Release 11.1.0.6.0 - Production on Tue Mar 18 15:43:48 2008 Copyright (c) 1982, 2007, Oracle.





Practice 11-3: Using Automatic SQL Tuning (continued) Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> SQL> SQL> PL/SQL procedure successfully completed.

SQL> SQL> WINDOW ------------------------------------------------------------------------------TUESDAY_WINDOW SQL> SQL> SQL> SQL> SQL> SQL> System altered.

2

SQL> SQL> > PL/SQL procedure successfully completed. SQL> SQL> > PL/SQL procedure successfully completed. SQL> SQL> PL/SQL procedure successfully completed. SQL> SQL> SQL> SQL> SQL> SQL> PL/SQL procedure successfully completed. SQL> SQL> 2 3 4 5 6 7 8 14 15 16 17 18 19 20 21 22 PL/SQL procedure successfully completed.

9

10

11

12

SQL> SQL> 2 System altered. SQL> SQL> SQL> SQL> SQL> SQL> SQL> > PL/SQL procedure successfully completed. SQL> SQL> > PL/SQL procedure successfully completed. SQL> SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options Tue Mar 18 15:44:50 GMT-7 2008 [oracle@edrsr33p1-orcl Automatic_SQL_Tuning]$ -------------------------------------------------------------#!/bin/bash


13


SQL> SQL> SQL> SQL> 2 3 4 PL/SQL procedure successfully completed.

Practice 11-3: Using Automatic SQL Tuning (continued) cd /home/oracle/solutions/Automatic_SQL_Tuning export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin date

set echo on exec dbms_workload_repository.create_snapshot; variable window varchar2(20); begin select upper(to_char(sysdate,'fmday'))||'_WINDOW' into :window from dual; end; / print window; --- Open the corresponding maintenance window, but with other clients disabled -alter system set "_enable_automatic_maintenance"=1 / exec dbms_auto_task_admin.disable( 'auto optimizer stats collection', null, :window); exec dbms_auto_task_admin.disable( 'auto space advisor', null, :window); exec dbms_scheduler.open_window(:window, null, true); --- Close the maintenance window when sqltune is done -exec dbms_lock.sleep(60); declare running number; begin loop select count(*)



sqlplus / as sysdba <
Practice 11-3: Using Automatic SQL Tuning (continued) into from where

running dba_advisor_executions task_name = 'SYS_AUTO_SQL_TUNING_TASK' and status = 'EXECUTING';

if (running = 0) then exit; end if; dbms_lock.sleep(60); end loop;

end; / alter system set "_enable_automatic_maintenance"=0 / --- Re-enable the other guys so they look like they are enabled in EM. -- Still they will be disabled because we have set the underscore. -exec dbms_auto_task_admin.enable( 'auto optimizer stats collection', null, :window); exec dbms_auto_task_admin.enable( 'auto space advisor', null, :window);

FIN! date

4) Execute the run_workload_stream.sh script again. What do you observe? a) You should see that the execution time for run_workload_stream.sh is much faster than the original execution. This is probably due to the fact that Automatic SQL Tuning implemented a profile for your statement automatically. ./run_workload_stream.sh [oracle@edrsr33p1-orcl Automatic_SQL_Tuning]$ ./run_workload_stream.sh Tue Mar 18 15:46:42 GMT-7 2008 SQL*Plus: Release 11.1.0.6.0 - Production on Tue Mar 18 15:46:42 2008 Copyright (c) 1982, 2007, Oracle.


Connected to:



dbms_scheduler.close_window(:window);

Practice 11-3: Using Automatic SQL Tuning (continued) Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> SQL> SQL> no rows selected SQL> no rows selected SQL> no rows selected

SQL> no rows selected SQL> no rows selected SQL> no rows selected SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options Tue Mar 18 15:46:42 GMT-7 2008 [oracle@edrsr33p1-orcl Automatic_SQL_Tuning]$ -----------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/AST export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin date sqlplus ast/ast <


...

Practice 11-3: Using Automatic SQL Tuning (continued) select /*+ USE_NL(s c) FULL(s) FULL(c) AST */ c.cust_id, sum(s.quantity_sold) from sh.sales s, sh.customers c where s.cust_id = c.cust_id and c.cust_id < 2 group by c.cust_id; FIN! date

5) Force the creation of an Automatic Workload Repository (AWR) snapshot. ./create_snapshot.sh



Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> SQL> SQL> PL/SQL procedure successfully completed. SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Automatic_SQL_Tuning]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Automatic_SQL_Tuning export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin sqlplus / as sysdba <


SQL*Plus: Release 11.1.0.6.0 - Production on Tue Mar 18 15:51:19 2008

Practice 11-3: Using Automatic SQL Tuning (continued) 6) How would you confirm that a SQL Profile was automatically implemented? a) In Oracle Enterprise Manager, locate the Automatic SQL Tuning summary page under Server > Automated Maintenance Tasks > Automatic SQL Tuning. The task has already run in one maintenance window and has results ready to be viewed. b) View the tuning results. c) Look at the graphs on the Task Activity Summary page.

e) Click View Report to see a detailed SQL-level report. Find the SQL that ran in the AST schema. Note the green check mark meaning that the profile was implemented. f) Click the corresponding option button and then View Recommendations. g) Click the Compare Explain Plans eyeglass icon for the SQL Profile entry. h) View the old and new explain plans for the query. i) Then click the “Recommendations for SQL_ID” locator link to return to the previous screen. j) Investigate a SQL profile. While still on the “Recommendations for SQL_ID” page, click the SQL text to go to the SQL Details page for this SQL. k) This takes you to the Tuning History tab. Note the link to SYS_AUTO_SQL_TUNING_TASK that is there to show that the SQL was tuned by this tuning task. l) Look at the Plan Control subpage and note that a profile was created automatically for this SQL. The AUTO type means it was automatically created. m) Click the Statistics tab to take a look at the execution history for this SQL. n) Depending on the speed of your machine, you may not see two hash values. If that is the case, ignore this step and the following one. Select Real Time: Manual Refresh from the View Data and then each of possible two Plan Hash Values from the corresponding drop-down list. Choose one after the other and wait for the page to refresh each time. o) Depending on the speed of your environment, you should see one statement with a relatively high elapsed time per execution, and one with very low elapsed time per execution. This shows the improved plan. If you select All from the Plan Hash Values drop-down list, you might not be able to see the execution corresponding to the statement after tuning in the Summary graph. This might be because the workload was too short to execute. 7) Generate a text report for more indepth information. From the command line, execute the get_task_report.sh script. What do you observe?



d) Focus on understanding the pie chart and the bar graph next to it. You should be able to get a feeling for the general finding breakdown, as well as the number of SQL profiles implemented by the task.

Practice 11-3: Using Automatic SQL Tuning (continued) a) Note the first queries that fetch execution name and object number from the advisor schema, followed by the final query that gets the text report. In the text report, look for the section about the SQL profile finding and peruse the Validation Results section. This shows you the execution statistics observed during test-execute and allows you to get a better idea about the profile’s quality. You can also use the report_auto_tuning_task API to get reports that span multiple executions of the task. ./get_task_report.sh



Connected to: Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> Session altered. SQL> SQL> 2 3 4 EXECUTION_NAME STATUS EXECUTION_START ------------------------------ ----------- ------------------EXEC_1 COMPLETED 03/18/2008 15:43:54 SQL> SQL> SQL> SQL> 2 3 4 5 PL/SQL procedure successfully completed.

6

7

SQL> SQL> LAST_EXEC ------------------------------------------------------------------------------EXEC_1 SQL> SQL> SQL> SQL> SQL> SQL> SQL> SQL> 8 9 10 PL/SQL procedure successfully completed.

2

3

4

5

6

7

SQL> SQL> OBJ_ID ---------3 SQL> SQL> SQL> SQL> SQL> SQL> 2 3 GENERAL INFORMATION SECTION -----------------------------------------------------------------------------Tuning Task Name : SYS_AUTO_SQL_TUNING_TASK Tuning Task Owner : SYS



[oracle@edrsr33p1-orcl Automatic_SQL_Tuning]$ ./get_task_report.sh

Practice 11-3: Using Automatic SQL Tuning (continued) : Automatic High-Load SQL : : : : : : : :

COMPREHENSIVE 3600 1200 COMPLETED 03/18/2008 15:43:54 03/18/2008 15:44:14 4 27

-----------------------------------------------------------------------------Object ID : 3 Schema Name: AST SQL ID : by9m5m597zh19 SQL Text : select /*+ USE_NL(s c) FULL(s) FULL(c) AST */ c.cust_id, sum(s.quantity_sold) from sh.sales s, sh.customers c where s.cust_id = c.cust_id and c.cust_id < 2 group by c.cust_id -----------------------------------------------------------------------------FINDINGS SECTION (2 findings) -----------------------------------------------------------------------------1- SQL Profile Finding (see explain plans section below) -------------------------------------------------------A potentially better execution plan was found for this statement. SQL profile "SYS_SQLPROF_01463043cc730000" was created automatically for this statement. Recommendation (estimated benefit: 98.62%) ------------------------------------------ An automatically-created SQL profile is present on the system. Name: SYS_SQLPROF_01463043cc730000 Status: ENABLED Validation results -----------------The SQL profile was tested by executing both its plan and the original plan and measuring their respective execution statistics. A plan may have been only partially executed if the other could be run to completion in less time. Original Plan

With SQL Profile

%

-------------

----------------

--------

COMPLETE

COMPLETE

Improved -Completion Status:



Workload Type Workload Scope Global Time Limit(seconds) Per-SQL Time Limit(seconds) Completion Status Started at Completed at Number of Candidate SQLs Cumulative Elapsed Time of SQL (s)

Elapsed Time(ms): 100% CPU Time(ms): 100% User I/O Time(ms): Buffer Gets: 98.61% Disk Reads: Direct Writes: Rows Processed: Fetches: Executions:

182

0

182

0

0 3177

0 44

0 0 0 0 1

0 0 0 0 1

2- Index Finding (see explain plans section below) -------------------------------------------------The execution plan of this statement can be improved by creating one or more indices. Recommendation (estimated benefit: 90.97%) ------------------------------------------ Consider running the Access Advisor to improve the physical schema design or creating the recommended index. create index SH.IDX$$_00010001 on SH.SALES("CUST_ID"); Rationale --------Creating the recommended indices significantly improves the execution plan of this statement. However, it might be preferable to run "Access Advisor" using a representative SQL workload as opposed to a single statement. This will allow to get comprehensive index recommendations which takes into account index maintenance overhead and additional space consumption. -----------------------------------------------------------------------------EXPLAIN PLANS SECTION -----------------------------------------------------------------------------1- Original With Adjusted Cost -----------------------------Plan hash value: 4005616876 ------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | Pstart| Pstop | -------------------------------------------------------------------------------



Practice 11-3: Using Automatic SQL Tuning (continued)

------------------| 0 | SELECT STATEMENT | | 1 | 13 | 902 (2)| 00:00:1 1 | | | | 1 | HASH GROUP BY | | 1 | 13 | 902 (2)| 00:00:1 1 | | | | 2 | NESTED LOOPS | | 1 | 13 | 901 (2)| 00:00:1 1 | | | |* 3 | TABLE ACCESS FULL | CUSTOMERS | 1 | 5 | 405 (1)| 00:00:0 5 | | | | 4 | PARTITION RANGE ALL| | 1 | 8 | 495 (3)| 00:00:0 6 | 1 | 28 | |* 5 | TABLE ACCESS FULL | SALES | 1 | 8 | 495 (3)| 00:00:0 6 | 1 | 28 | ------------------------------------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------3 - filter("C"."CUST_ID"<2) 5 - filter("S"."CUST_ID"<2 AND "S"."CUST_ID"="C"."CUST_ID") 2- Using SQL Profile -------------------Plan hash value: 3070788227 --------------------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | Pstart| Pstop | --------------------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 13 | 55 (2)| 00:00:01 | | | | 1 | HASH GROUP BY | | 1 | 13 | 55 (2)| 00:00:01 | | | | 2 | NESTED LOOPS | | 1 | 13 | 54 (0)| 00:00:01 | | | | 3 | PARTITION RANGE ALL | | 1 | 8 | 54 (0)| 00:00:01 | 1 | 28 | | 4 | TABLE ACCESS BY LOCAL INDEX ROWID| SALES | 1 | 8 | 54 (0)| 00:00:01 | 1 | 28 |



Practice 11-3: Using Automatic SQL Tuning (continued)

Practice 11-3: Using Automatic SQL Tuning (continued) | |

5 |

|* |

6 |

BITMAP CONVERSION TO ROWIDS

|

|

| |

| | | BITMAP INDEX RANGE SCAN

| SALES_CUST_BIX |

|

| | 1 | 28 | |* 7 | INDEX UNIQUE SCAN | CUSTOMERS_PK | 1 | 5 | 0 (0)| 00:00:01 | | | ---------------------------------------------------------------------------------------------------------------------

6 - access("S"."CUST_ID"<2) filter("S"."CUST_ID"<2) 7 - access("S"."CUST_ID"="C"."CUST_ID") filter("C"."CUST_ID"<2) 3- Using New Indices -------------------Plan hash value: 1871796534 --------------------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | Pstart| Pstop | --------------------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 13 | 5 (0)| 00:00:01 | | | | 1 | SORT GROUP BY NOSORT | | 1 | 13 | 5 (0)| 00:00:01 | | | | 2 | NESTED LOOPS | | | | | | | | | 3 | NESTED LOOPS | | 1 | 13 | 5 (0)| 00:00:01 | | | |* 4 | INDEX RANGE SCAN | CUSTOMERS_PK | 1 | 5 | 2 (0)| 00:00:01 | | | |* 5 | INDEX RANGE SCAN | IDX$$_00010001 | 1 | | 2 (0)| 00:00:01 | | | | 6 | TABLE ACCESS BY GLOBAL INDEX ROWID| SALES | 1 | 8 | 3 (0)| 00:00:01 | ROWID | ROWID | -------------------------------------------------------------------------------




Practice 11-3: Using Automatic SQL Tuning (continued) --------------------------------------Predicate Information (identified by operation id): --------------------------------------------------4 - access("C"."CUST_ID"<2) 5 - access("S"."CUST_ID"="C"."CUST_ID") filter("S"."CUST_ID"<2)

SQL> SQL> Disconnected from Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - Production With the Partitioning, Oracle Label Security, OLAP, Data Mining and Real Application Testing options [oracle@edrsr33p1-orcl Automatic_SQL_Tuning]$ -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Automatic_SQL_Tuning export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin sqlplus / as sysdba <


------------------------------------------------------------------------------

Practice 11-3: Using Automatic SQL Tuning (continued) end; / print :last_exec --- Find the object ID for query AST with sql_id by9m5m597zh19 --

begin select into from where

object_id :obj_id dba_advisor_objects task_name = 'SYS_AUTO_SQL_TUNING_TASK' and execution_name = :last_exec and type = 'SQL' and attr1 = 'by9m5m597zh19';

end; / print :obj_id --- Get a text report to drill down on this one query -set pagesize 0 select dbms_sqltune.report_auto_tuning_task( :last_exec, :last_exec, 'TEXT', 'TYPICAL', 'ALL', :obj_id) from dual; FIN!

8) Investigate how to configure Automatic SQL Tuning using Enterprise Manager. a) Back in EM, go to the Automated Maintenance Tasks page. b) The chart here shows times in the past when each client was executed, and times in the future when they are scheduled to run again. c) Modify the graph’s begin and end points with the widgets at the upper right. d) Click the Configure button. e) This brings you to the Automated Maintenance Tasks Configuration page. f) From this page, you can disable individual clients and change which windows they run in. g) Disable the Automatic SQL Tuning client entirely, click Apply, and then click the locator link to return to the last page. h) Note that no light blue bars appear for Automatic SQL Tuning in the future. i) Return to the configuration page, enable the task again, and click Apply to undo your changes.



variable obj_id number;

Practice 11-3: Using Automatic SQL Tuning (continued) j) Click the Automatic SQL Tuning link on the Automated Maintenance Tasks Configuration page. k) This takes you to the page where you can configure the task itself, and set beyond when it will run. l) Note that there are more fine-grained controls here, such as one that allows the task to run but not implement profiles, and one that allows you to control the maximum number of profiles created per run.

a) Note the first action. You changed the total time limit for the task. Instead of running for an unlimited amount of time (still bound by the maintenance window boundaries), it now runs for a maximum of one hour. The execute_tuning_task API call runs the task immediately, in the foreground. Use this to run the task yourself whenever you want. ./manual_config.sh -------------------------------------------------------------#!/bin/bash cd /home/oracle/solutions/Automatic_SQL_Tuning export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin sqlplus / as sysdba <


9) Investigate how to configure Automatic SQL Tuning using PL/SQL. From your terminal session, execute the manual_config.sh script. What does it do?

Practice 11-3: Using Automatic SQL Tuning (continued) select parameter_value from dba_advisor_parameters where task_name = 'SYS_AUTO_SQL_TUNING_TASK' and parameter_name = 'TIME_LIMIT'; --- Run the task immediately -exec dbms_sqltune.execute_tuning_task('SYS_AUTO_SQL_TUNING_TASK');

10) Note: In your case, the task executes quickly because the workload to take into account is really small. However, you could use the interrupt_task.sh script from another session to stop the task, should it last too long. [oracle@edrsr33p1-orcl Automatic_SQL_Tuning]$ cat interrupt_task.sh #!/bin/bash cd /home/oracle/solutions/Automatic_SQL_Tuning export ORACLE_SID=orcl export ORACLE_HOME=/u01/app/oracle/product/11.1.0/db_1 export PATH=/u01/app/oracle/product/11.1.0/db_1/bin:/bin:/usr/bin:/usr/loca l/bin:/usr/X11R6/bin:/usr/java/jdk1.5.0_11/bin sqlplus / as sysdba <
11) Ensure that you disable automatic implementation of SQL profiles to clean up your environment. a) On the EM Server page, click Automated Maintenance Tasks. b) Check that Status is set to Enabled, and click Configure. c) Click the Configure button next to Automatic SQL Tuning. d) Select No for “Automatic Implementation of SQL Profiles.” e) Then, click Apply.



FIN!



Index

Access path 3-16, 3-17, 3-19, 3-23, 3-24, 3-28, 3-32, 4-2, 4-3, 4-4, 4-6, 4-8, 4-10, 4-14, 4-17, 4-29, 4-31, 4-33, 4-43, 4-47, 4-56, 4-71, 4-72, 5-49, 6-8, 6-14, 9-2, 9-9, 9-10, 9-11, 9-12, 9-13, 9-14, 9-17, 9-30, 11-5, 11-7, 11-10, 11-15 Action 1-11, 1-12, 1-22, 1-23, 2-7, 2-9, 2-13, 2-14, 2-15, 2-17, 2-18, 2-19, 3-3, 3-12, 3-25, 3-30, 4-3, 4-6, 4-30, 4-70, 6-14, 7-20, 7-22, 7-32, 8-8, 10-4, 10-8, 10-9, 10-10, 10-13, 10-14, 11-3, 11-15, 11-21, 11-24, 11-25 Adaptive Cursor Sharing 8-2, 8-12, 8-13, 8-14, 8-15, 8-16, 8-17, 8-18, 8-19, 8-20, 8-21 ADDM 2-6, 2-8, 2-9, 2-10, 2-11, 2-14, 2-15, 5-27, 5-28, 11-4, 11-9, 11-12, 11-14, 11-26, 11-38 ADR 10-5, 10-14, 10-15 AGGREGATE 1-6, 1-17, 1-18, 2-19, 3-5, 3-20, 3-21, 3-29, 3-30, 4-20, 4-27, 4-30, 4-31, 4-48, 4-52, 4-53, 5-26, 5-38, 5-47, 6-10, 10-19, 10-25, 10-28, 10-29 ALL_ROWS 3-32, 3-33, 5-14, 9-4, 9-8, 9-10, 10-26, 10-28, 10-29, 11-7 ALTER 1-8, 3-3, 3-11, 3-28, 4-12, 4-20, 4-24, 4-27, 4-37, 4-38, 4-50, 5-11, 5-25, 5-44, 7-8, 7-22, 7-26, 8-11, 8-12, 9-10, 10-12, 11-11 ALTER SESSION 3-3, 5-44, 8-11, 8-12, 9-10, 10-12 ALTER SYSTEM 3-3, 7-22, 8-11 AND-EQUAL 4-25 Anti Join 4-61, 4-65 APPEND 2-20, 4-68, 9-23 Architecture 1-1, 1-2, 1-3, 1-12, 1-19, 1-20, 8-14, 8-15 Ascending 4-10, 4-11, 4-15, 4-16, 4-17, 9-12, 9-14 ASH 1-14, 1-17, 1-19, 2-6, 2-8, 2-9, 3-27, 3-28, 3-30, 4-4, 4-5, 4-11, 4-24, 4-44, 4-45, 4-46, 4-47, 4-48, 4-51, 4-54, 4-58, 4-59, 4-62, 4-63, 4-64, 4-65, 4-67, 4-70, 5-11, 5-12, 5-14, 5-20, 5-21, 5-22, 5-23, 5-24, 5-25, 5-26, 5-27, 5-30, 5-32, 5-37, 5-44, 5-47, 5-49, 6-6, 6-12, 6-13, 6-16, 8-3, 9-11, 9-22, 9-29, 11-18, 11-26

Oracle Database 11g: SQL Tuning Workshop Index - 2


A

AST 1-5, 1-7, 1-16, 2-3, 2-6, 2-18, 2-19, 3-5, 3-11, 3-12, 3-16, 3-17, 3-25, 3-28, 3-29, 3-30, 3-33, 4-4, 4-5, 4-6, 4-7, 4-9, 4-10, 4-13, 4-19, 4-20, 4-21, 4-24, 4-27, 4-28, 4-29, 4-32, 4-36, 4-40, 4-45, 4-46, 4-67, 4-69, 5-4, 5-9, 5-11, 5-13, 5-19, 5-24, 5-25, 5-26, 5-27, 5-35, 5-36, 5-37, 5-38, 5-39, 5-44, 5-45, 5-46, 6-7, 6-10, 6-14, 7-16, 7-19, 7-26, 7-33, 8-3, 8-8, 8-10, 9-3, 9-7, 9-10, 9-11, 9-14, 9-15, 9-20, 9-21, 9-22, 9-23, 9-24, 9-28, 9-30, 9-31, 10-17, 10-27, 11-3, 11-5, 11-7, 11-16, 11-17, 11-18, 11-27, 11-28, 11-29, 11-30, 11-31, 11-33, 11-37 AUDIT 3-3 Automatic 1-8, 1-14, 1-15, 1-16, 1-17, 1-18, 1-24, 2-6, 2-7, 2-8, 2-10, 2-11, 2-12, 2-15, 2-20, 3-30, 3-33, 4-10, 5-7, 5-10, 5-15, 5-27, 5-28, 5-29, 5-30, 5-35, 6-7, 6-10, 7-3, 7-4, 7-13, 7-15, 7-21, 7-24, 7-25, 7-26, 7-27, 7-34, 7-36, 8-12, 8-13, 8-16, 8-19, 10-6, 10-8, 11-2, 11-3, 11-4, 11-5, 11-6, 11-7, 11-8, 11-11, 11-12, 11-15, 11-26, 11-27, 11-28, 11-29, 11-30, 11-31, 11-32, 11-33, 11-34, 11-35, 11-36, 11-37, 11-38 Automatic SQL tuning 2-6, 11-2, 11-27, 11-28, 11-30, 11-31, 11-32, 11-33, 11-34, 11-35, 11-36, 11-37, 11-38 Automatic Tuning Optimizer 11-3, 11-5, 11-6, 11-7 AUTOTRACE 5-4, 5-6, 5-15, 5-16, 5-17, 5-18, 5-19, 9-15, 10-25 AWR 2-6, 2-8, 2-9, 2-12, 5-4, 5-6, 5-21, 5-27, 5-28, 5-29, 5-30, 5-31, 5-32, 5-33, 5-34, 11-12, 11-14, 11-27, 11-32 awrsqrpt 2-8, 5-34 B B*tree 3-19, 4-10, 4-11, 4-12, 4-18, 4-26, 4-27, 4-30, 4-46, 7-4, 7-8 background process 1-2, 1-3, 1-4, 1-6, 1-8, 1-15, 1-18, 1-20, 1-25, 10-12 BIND 2-14, 2-16, 2-22, 2-23, 2-24, 2-25, 3-6, 3-7, 3-11, 3-12, 3-13, 4-23, 5-14, 5-15, 6-8, 8-1, 8-2, 8-4, 8-5, 8-6, 8-7, 8-8, 8-11, 8-12, 8-13, 8-14, 8-15, 8-16, 8-17, 8-18, 8-19, 8-20, 8-21, 9-24, 10-10, 10-11, 10-12, 10-15, 10-16, 10-17, 11-12 bind peeking 5-15, 8-2, 8-13, 8-14, 8-20, 8-21



A

Bind variable 2-14, 2-16, 2-22, 2-23, 2-24, 2-25, 3-7, 5-15, 6-8, 8-1, 8-2, 8-4, 8-5, 8-6, 8-7, 8-8, 8-11, 8-12, 8-13, 8-14, 8-16, 8-18, 8-19, 8-20, 9-24, 10-17 Bind-aware 8-14, 8-15, 8-16, 8-17 Bind-sensitive 8-14, 8-16 Bitmap 1-14, 3-30, 4-4, 4-10, 4-11, 4-18, 4-20, 4-30, 4-31, 4-32, 4-33, 4-34, 4-35, 4-36, 4-39, 5-26, 6-5, 6-7, 6-8, 6-9, 6-10, 6-11, 6-13, 6-15, 6-16, 6-18, 6-19, 6-20, 6-21, 7-9, 9-12, 9-14, 9-15, 9-16 BITMAP AND 4-33, 4-34, 6-11, 6-13, 6-16, 9-16 BITMAP CONVERSION 4-31, 4-33, 4-34, 6-13, 6-16, 9-16 Bitmap create area 1-14 BITMAP INDEX 4-4, 4-10, 4-11, 4-20, 4-30, 4-31, 4-32, 4-33, 4-34, 4-35, 4-39, 6-5, 6-7, 6-8, 6-9, 6-10, 6-11, 6-13, 6-15, 6-16, 6-18, 6-19, 6-20, 6-21, 7-9, 9-12, 9-15, 9-16 Bitmap Join Index 4-11, 4-35, 6-15, 6-16, 6-18, 6-19, 6-20, 6-21, 9-12 BITMAP KEY ITERATION 4-34, 6-10, 6-13, 6-16 BITMAP MERGE 1-14, 3-30, 4-34, 6-11, 6-13, 6-16, 9-16 Bitmap merge area 1-14 BITMAP MINUS 4-34 BITMAP OR 6-16, 9-16 Branch 4-12, 4-20, 4-21, 4-22, 4-46, 4-68, 5-41, 5-48 Buffer cache 1-6, 1-7, 1-10, 1-11, 1-15, 1-16, 1-18, 2-15, 3-5, 3-27, 3-30, 3-32, 4-5, 4-45, 4-49, 5-18, 9-24 BUFFER SORT 4-49, 4-60, 6-13, 6-16 C CACHE 1-6, 1-7, 1-9, 1-10, 1-11, 1-12, 1-15, 1-16, 1-18, 2-15, 3-5, 3-9, 3-14, 3-27, 3-29, 3-30, 3-31, 3-32, 4-5, 4-45, 4-49, 4-70, 4-72, 5-4, 5-18, 5-20, 5-23, 5-24, 5-25, 5-32, 7-20, 8-3, 8-4, 8-16, 8-19, 9-24, 9-25, 10-16, 10-23, 10-26, 10-28, 10-29, 11-12, 11-17, 11-21 Cardinality 2-3, 3-24, 3-26, 5-3, 5-38, 7-5, 7-12, 7-24, 7-31, 9-24, 11-7



B

Cartesian 2-3, 4-49, 4-60, 5-49, 11-11 Child 5-3, 5-20, 5-21, 5-23, 5-24, 5-25, 5-40, 5-41, 5-43, 5-44, 5-45, 5-46, 5-48, 8-12, 8-13, 8-15 Client 1-4, 1-12, 3-5, 3-8, 3-9, 3-10, 5-18, 5-19, 10-3, 10-4, 10-7, 10-8, 10-9, 10-10, 10-13, 10-14, 10-15 CLIENT_IDENTIFIER 10-8, 10-10, 10-14 CLOSE 1-5, 3-3, 3-6, 3-7, 3-12, 3-13, 3-28, 5-44, 9-5, 10-16, 10-27 Cluster 1-3, 1-22, 2-12, 2-19, 4-4, 4-6, 4-8, 4-10, 4-13, 4-44, 4-45, 4-46, 4-47, 4-56, 7-4, 7-6, 7-8, 7-9, 9-11, 10-6 Clustering factor 4-45, 4-46, 7-4, 7-6, 7-8, 7-9 COMMENT 2-24, 3-3, 9-3, 9-5, 9-6 COMMIT 1-11, 1-22, 2-13, 3-3, 3-12, 10-16, 10-18 Composite 4-10, 4-21, 4-23, 4-28, 4-36, 4-44, 4-55, 5-37 CONCATENATION 4-50, 4-66, 4-68, 9-17 CONNECT 1-3, 1-4, 1-5, 1-6, 1-7, 1-19, 2-13, 2-14, 2-22, 2-25, 3-3, 3-5, 3-21, 4-12, 5-10, 5-15, 9-27, 10-6, 10-7, 10-8, 10-20 Connection 1-4, 1-5, 2-13, 2-14, 2-22, 2-25, 10-6, 10-7, 10-8 Constraint 2-18, 2-19, 2-20, 3-20, 4-10, 4-14, 4-20, 4-27, 4-35, 4-39, 4-40, 7-7, 11-3 control file 1-15, 1-19 CONTROL_MANAGEMENT_PACK_ACCESS 5-35, 9-25 Cost 1-14, 2-3, 2-4, 3-16, 3-18, 3-19, 3-24, 3-26, 3-27, 3-28, 3-30, 3-32, 3-33, 3-34, 4-4, 4-5, 4-7, 4-8, 4-9, 4-11, 4-14, 4-15, 4-16, 4-17, 4-18, 4-19, 4-20, 4-23, 4-25, 4-26, 4-29, 4-31, 4-34, 4-39, 4-40, 4-45, 4-46, 4-47, 4-49, 4-50, 4-51, 4-52, 4-53, 4-54, 4-55, 4-58, 4-59, 4-60, 4-64, 5-3, 5-11, 5-12, 5-14, 5-25, 5-32, 5-38, 6-3, 6-7, 6-12, 6-14, 6-17, 7-3, 7-5, 7-6, 7-8, 7-9, 7-16, 7-20, 7-31, 7-32, 9-8, 9-10, 9-12, 9-15, 9-17, 9-19, 9-24, 9-25, 9-29, 10-17, 11-7, 11-16, 11-17, 11-21, 11-22, 11-25, 11-30 COUNT STOPKEY 4-52



C

CPU 1-8, 2-3, 2-12, 3-27, 4-5, 4-8, 4-26, 4-30, 4-31, 4-47, 4-51, 4-52, 4-58, 4-60, 4-64, 5-11, 5-12, 5-14, 5-25, 5-27, 5-32, 5-35, 5-37, 5-38, 5-39, 7-3, 7-4, 7-20, 7-26, 8-13, 8-17, 9-29, 10-16, 10-24, 10-25, 10-28, 10-29, 11-4, 11-14, 11-21, 11-29, 11-30 CREATE 1-4, 1-5, 1-6, 1-8, 1-14, 1-21, 1-22, 1-24, 2-11, 2-19, 2-20, 2-24, 3-3, 3-5, 3-7, 3-8, 3-9, 3-11, 3-18, 3-21, 3-22, 3-30, 4-6, 4-10, 4-14, 4-15, 4-16, 4-17, 4-18, 4-19, 4-20, 4-23, 4-24, 4-26, 4-27, 4-28, 4-29, 4-35, 4-36, 4-38, 4-39, 4-40, 4-41, 4-44, 4-45, 4-46, 4-47, 4-51, 4-67, 5-7, 5-10, 5-15, 5-29, 5-33, 6-7, 6-14, 6-15, 6-18, 6-19, 6-20, 6-21, 7-4, 7-11, 7-13, 7-15, 7-16, 7-17, 7-18, 7-19, 7-21, 7-26, 7-29, 9-28, 10-7, 10-8, 10-10, 10-20, 10-27, 10-29, 10-31, 11-5, 11-7, 11-8, 11-9, 11-10, 11-12, 11-14, 11-15, 11-16, 11-21, 11-25, 11-27, 11-28, 11-29, 11-36 Cube 8-14, 8-15, 8-16 Cursor 1-14, 2-14, 2-16, 2-22, 2-23, 2-24, 2-25, 3-7, 3-8, 3-12, 3-13, 3-29, 5-4, 5-6, 5-20, 5-21, 5-22, 5-23, 5-24, 5-25, 5-26, 5-32, 5-44, 7-26, 8-2, 8-3, 8-4, 8-8, 8-9, 8-10, 8-11, 8-12, 8-13, 8-14, 8-15, 8-16, 8-17, 8-18, 8-19, 8-20, 8-21, 9-24, 10-16, 10-17, 10-27, 11-12, 11-29 Cursor Sharing 2-16, 2-25, 3-29, 8-2, 8-3, 8-4, 8-8, 8-9, 8-10, 8-12, 8-13, 8-14, 8-15, 8-16, 8-17, 8-18, 8-19, 8-20, 8-21 CURSOR_SHARING 2-24, 3-29, 8-11, 8-12, 8-19, 8-21, 9-24, 11-29 CURSOR_SHARING_EXACT 8-11, 9-24 D Data block 1-7, 1-22, 1-23, 2-15, 4-4, 4-7, 4-12, 4-21, 4-44, 4-47, 4-49, 4-56, 5-18, 7-5, 7-6, 7-7, 7-28, 10-25, 10-29 Data dictionary cache 1-9, 3-5, 10-26 data file 1-7, 1-10, 1-11, 1-15, 1-19, 1-21, 1-23, 10-25 Database writer 1-7, 1-10, 1-15 DB_FILE_MULTIBLOCK_READ_COUNT 3-29, 4-5, 4-6, 4-20, 7-5 DBA_HIST_ACTIVE_SESS_HISTORY 5-31 DBA_HIST_BASELINE DBA_HIST_DATABASE_INSTANCE 5-31 DBA_HIST_SNAPSHOT 5-29, 5-30, 5-31 DBA_HIST_SQL_PLAN 5-4, 5-31



C

DBA_HIST_WR_CONTROL 5-30, 5-31 DBA_IND_STATISTICS 7-6, 7-8 DBA_TAB_COL_STATISTICS 3-25, 7-10 DBA_TAB_STATISTICS 3-25, 7-5, 7-34 DBA_TABLES 3-25 DBMS_APPICATION_INFO 10-4 DBMS_MONITOR 5-4, 10-4, 10-10, 10-11, 10-12, 10-13, 10-15 DBMS_SERVICE 10-4 DBMS_SESSION 10-4, 10-8, 10-10, 10-12, 10-15 DBMS_SQLTUNE 5-35, 5-37, 11-7, 11-30 DBMS_STATS 2-15, 7-3, 7-13, 7-15, 7-17, 7-18, 7-19, 7-20, 7-22, 7-23, 7-24, 7-25, 7-26, 7-28, 7-29, 7-30, 7-34, 11-6 DBMS_WORKLOAD_REPOSITORY 5-28, 5-29, 5-30, 5-33, 11-32 DBMS_XPLAN 5-6, 5-11, 5-12, 5-14, 5-25, 5-32, 5-33, 5-34, 5-44, 9-29 DECLARE 3-3, 4-26, 7-16 DEFINE 1-19, 3-3, 3-6, 3-7, 3-10, 3-12, 3-22, 3-26, 3-34, 4-10, 4-18, 4-27, 4-29, 4-44, 4-54, 4-55, 6-2, 6-22, 7-5, 7-19, 7-20, 8-5, 8-6, 9-24, 9-26, 10-5, 10-7, 10-9, 10-10, 11-20, 11-31, 11-32 DELETE 1-8, 1-19, 3-3, 3-11, 3-12, 4-5, 4-18, 5-3, 5-15, 5-36, 7-25, 7-26, 7-28, 7-33, 7-34, 8-15, 9-5, 9-6, 9-28, 10-20, 10-25, 10-29 Descending 4-10, 4-11, 4-13, 4-15, 4-16, 4-17, 9-12, 9-13, 10-19 DESCRIBE 1-2, 1-25, 2-2, 2-26, 3-2, 3-3, 3-6, 3-7, 3-10, 3-35, 3-36, 4-16, 6-10, 6-11, 7-3, 7-26, 7-27, 9-21, 10-5, 11-19 DIAGNOSTIC_DEST 10-5 Dimension 2-12, 4-61, 6-3, 6-4, 6-6, 6-7, 6-8, 6-9, 6-10, 6-11, 6-12, 6-13, 6-14, 6-15, 6-16, 6-17, 6-18, 6-20, 6-21, 10-6, 11-17, 11-21 Dispatcher 1-4, 1-5 Domain 4-10, 4-11, 9-12, 9-14 DRIVING_SITE 9-22 DROP 1-8, 3-3, 4-10, 4-27, 4-37, 4-38, 4-39, 4-40, 5-10, 5-29, 5-30, 10-20, 10-27, 11-16, 11-17



D

D dynamic sampling 3-25, 3-33, 3-34, 7-2, 7-17, 7-19, 7-24, 7-31, 7-32, 7-33, 7-34, 7-35, 9-24, 11-6, 11-7 Dynamic SQL 2-14, 2-16 DYNAMIC_SAMPLING 3-25, 3-32, 3-33, 7-17, 7-31, 7-32, 7-33, 9-24, 9-25 Equi 1-7, 1-16, 1-17, 2-2, 2-5, 2-6, 2-7, 2-8, 2-14, 2-15, 2-17, 2-18, 2-19, 2-20, 2-23, 2-25, 3-7, 3-10, 3-18, 3-19, 3-20, 3-21, 3-22, 3-23, 4-7, 4-10, 4-28, 4-30, 4-35, 4-36, 4-39, 4-40, 4-48, 4-56, 4-58, 4-59, 4-61, 4-62, 4-65, 5-3, 5-15, 5-18, 5-19, 5-24, 5-34, 6-2, 6-4, 6-7, 6-19, 6-20, 6-22, 7-5, 7-6, 7-11, 7-17, 7-25, 7-27, 9-13, 9-24, 9-26, 10-20, 10-25, 10-28, 10-29, 11-4, 11-8, 11-11, 11-16, 11-22, 11-27, 11-29 Estimator 3-24, 3-25, 3-26, 3-27, 7-11 EXECUTE 1-10, 2-14, 2-15, 2-23, 2-25, 3-3, 3-4, 3-6, 3-7, 3-8, 3-9, 3-12, 3-13, 3-14, 3-19, 3-20, 3-24, 3-27, 4-11, 4-18, 4-50, 4-51, 4-58, 4-69, 4-70, 5-4, 5-7, 5-9, 5-10, 5-11, 5-18, 5-20, 5-25, 5-26, 5-32, 5-35, 5-38, 5-40, 5-41, 5-42, 5-43, 5-45, 5-46, 5-47, 5-48, 7-22, 7-23, 7-32, 8-4, 8-7, 8-8, 8-9, 8-10, 8-11, 8-14, 8-15, 9-11, 9-22, 9-24, 9-26, 10-10, 10-16, 10-17, 10-24, 10-25, 10-26, 10-27, 10-28, 10-29, 11-7, 11-30, 11-32, 11-36 Execution plan 2-3, 2-10, 2-11, 2-13, 2-15, 2-20, 2-21, 2-22, 3-16, 3-17, 3-18, 3-19, 3-20, 3-24, 3-26, 3-28, 3-32, 3-33, 4-2, 4-14, 4-16, 4-50, 4-55, 4-56, 4-59, 4-70, 5-1, 5-2, 5-3, 5-4, 5-5, 5-6, 5-7, 5-8, 5-9, 5-10, 5-11, 5-14, 5-15, 5-16, 5-17, 5-20, 5-24, 5-25, 5-31, 5-32, 5-33, 5-38, 5-39, 5-40, 5-41, 5-42, 5-43, 5-44, 5-45, 5-46, 5-47, 5-48, 5-49, 5-50, 5-51, 5-52, 6-3, 6-6, 6-14, 7-3, 7-31, 7-35, 8-3, 8-4, 8-9, 8-10, 8-13, 8-14, 8-15, 8-18, 9-3, 9-7, 9-8, 9-10, 9-14, 9-15, 9-16, 9-20, 9-22, 9-24, 9-26, 9-29, 9-30, 9-32, 10-16, 10-17, 10-20, 10-23, 10-26, 10-27, 10-30, 11-3, 11-4, 11-6, 11-26, 11-29, 11-30 Expansion 3-18, 3-19, 4-68, 9-17



E

E EXPLAIN PLAN 4-5, 4-51, 4-70, 5-3, 5-4, 5-6, 5-7, 5-8, 5-9, 5-10, 5-11, 5-12, 5-13, 5-15, 5-20, 5-40, 5-41, 5-44, 5-45, 5-50, 9-3, 9-29, 10-20, 10-27, 10-29 Expression Statistics 7-19 Extended statistics 7-4 Extent 1-21, 1-22, 1-23, 2-15, 5-48 FACT 2-13, 3-16, 3-29, 4-40, 4-45, 4-46, 4-61, 6-3, 6-4, 6-7, 6-8, 6-9, 6-10, 6-11, 6-12, 6-14, 6-15, 6-17, 6-18, 6-19, 7-4, 7-6, 7-8, 7-9, 7-14, 7-20, 7-29, 9-19, 9-20, 11-6, 11-7, 11-28 Fact table 6-3, 6-7, 6-8, 6-9, 6-10, 6-11, 6-12, 6-14, 6-15, 6-17, 6-18, 9-19 Fast full 3-29, 3-30, 4-4, 4-9, 4-13, 4-19, 4-20, 4-24, 4-27, 4-29, 4-36, 4-69, 8-10 FETCH 3-3, 3-6, 3-7, 3-8, 3-10, 3-12, 3-13, 4-14, 4-15, 4-56, 4-58, 4-59, 4-67, 5-17, 6-10, 7-8, 10-16, 10-17, 10-18, 10-24, 10-25, 10-28, 10-29 filter 3-25, 3-26, 4-5, 4-6, 4-14, 4-15, 4-17, 4-18, 4-19, 4-20, 4-21, 4-23, 4-25, 4-29, 4-31, 4-32, 4-45, 4-46, 4-47, 4-49, 4-50, 4-52, 4-55, 4-56, 4-57, 4-58, 4-59, 4-60, 4-62, 4-64, 4-66, 4-67, 4-68, 5-3, 5-11, 5-12, 5-25, 5-42, 5-44, 5-49, 6-6, 6-7, 6-9, 6-10, 6-14, 9-22, 10-18, 11-12, 11-17, 11-21 FILTER 3-25, 3-26, 4-5, 4-6, 4-14, 4-15, 4-17, 4-18, 4-19, 4-20, 4-21, 4-23, 4-25, 4-29, 4-31, 4-32, 4-45, 4-46, 4-47, 4-49, 4-50, 4-52, 4-55, 4-56, 4-57, 4-58, 4-59, 4-60, 4-62, 4-64, 4-66, 4-67, 4-68, 5-3, 5-11, 5-12, 5-25, 5-42, 5-44, 5-49, 6-6, 6-7, 6-9, 6-10, 6-14, 9-22, 10-18, 11-12, 11-17, 11-21 FIRST ROW 4-35, 4-46, 4-53, 4-58, 4-59, 4-60, 5-45, 9-10, 9-21, 9-22, 11-5 FIRST_ROWS 3-32, 3-33, 9-10, 11-7 foreground process 1-4, 5-18, 10-12 Foreign key 2-20, 4-35, 6-3, 6-4, 6-7, 6-9, 6-18 Frequency 5-28, 7-10, 7-11, 7-12, 7-13, 7-17, 7-25, 7-27



F

FULL 1-22, 2-10, 2-14, 2-15, 2-17, 3-17, 3-19, 3-28, 3-29, 3-30, 3-32, 4-3, 4-4, 4-5, 4-6, 4-9, 4-13, 4-19, 4-20, 4-24, 4-26, 4-27, 4-29, 4-34, 4-36, 4-45, 4-46, 4-47, 4-49, 4-51, 4-52, 4-53, 4-55, 4-56, 4-57, 4-58, 4-59, 4-60, 4-61, 4-62, 4-63, 4-64, 4-65, 4-67, 4-69, 4-70, 5-11, 5-12, 5-14, 5-25, 5-28, 5-30, 5-32, 5-33, 5-38, 5-39, 5-42, 5-44, 5-47, 5-49, 6-6, 6-13, 6-14, 6-16, 7-6, 7-8, 7-34, 8-5, 8-8, 8-10, 8-18, 9-7, 9-11, 9-12, 9-14, 9-19, 9-22, 9-24, 9-27, 9-29, 9-30, 10-17, 10-27, 10-28, 11-10, 11-18, 11-25, 11-27 Full Table Scan 2-14, 2-15, 3-17, 3-19, 3-29, 3-30, 3-32, 4-4, 4-5, 4-6, 4-9, 4-20, 4-45, 5-42, 5-44, 5-49, 6-14, 7-6, 7-8, 8-8, 8-18, 9-11, 9-12, 9-14, 9-22, 9-24, 9-29, 10-28, 11-10 Function based 2-4, 4-10, 4-41 Function-based 4-6, 4-11, 4-17, 4-18, 7-19, 9-14 G Gather 2-11, 4-11, 5-2, 5-3, 5-10, 5-22, 5-26, 5-51, 6-7, 7-2, 7-3, 7-4, 7-5, 7-6, 7-9, 7-11, 7-13, 7-15, 7-17, 7-19, 7-20, 7-21, 7-22, 7-23, 7-24, 7-25, 7-26, 7-27, 7-28, 7-29, 7-30, 7-31, 7-34, 7-36, 11-5, 11-6, 11-28, 11-29 Generator 3-24, 3-28 Global 1-3, 1-6, 1-14, 1-22, 5-7, 5-10, 5-37, 7-25, 7-26, 9-28, 10-10, 10-11, 11-10, 11-18, 11-30 GRANT 2-25, 3-3, 3-34, 5-15, 5-29 GROUP BY 2-4, 3-21, 3-25, 3-26, 4-15, 4-48, 4-51, 4-67, 4-70, 6-5, 6-6, 6-13, 6-16, 9-18, 9-22, 9-30 H Hard parse 2-23, 3-14, 3-18, 8-7, 8-13, 8-14, 8-15, 10-23 HASH 1-14, 1-17, 3-27, 3-28, 3-30, 4-4, 4-5, 4-24, 4-44, 4-45, 4-46, 4-47, 4-48, 4-51, 4-54, 4-58, 4-59, 4-62, 4-63, 4-64, 4-65, 4-67, 4-70, 5-11, 5-12, 5-14, 5-20, 5-21, 5-22, 5-23, 5-24, 5-25, 5-26, 5-32, 5-37, 5-44, 5-47, 5-49, 6-6, 6-12, 6-13, 6-16, 8-3, 9-11, 9-22, 9-29, 11-18 Hash Cluster 4-4, 4-44, 4-45, 4-46, 4-47



F

Hash Join 1-14, 3-28, 4-5, 4-24, 4-51, 4-54, 4-58, 4-59, 4-62, 4-63, 4-64, 4-65, 5-22, 5-32, 5-47, 6-6, 6-12, 6-13, 6-16, 9-22, 9-29 Hash join area 1-14 Height-Balanced 7-14, 7-15 High-load 2-11, 10-4, 11-3, 11-4, 11-9, 11-12, 11-14, 11-26 Hint 3-24, 3-30, 4-6, 4-9, 4-17, 4-20, 4-24, 4-25, 4-26, 4-65, 4-70, 5-14, 5-20, 5-22, 5-26, 5-35, 5-47, 6-8, 6-17, 7-31, 8-11, 9-1, 9-2, 9-3, 9-4, 9-5, 9-6, 9-7, 9-8, 9-9, 9-10, 9-11, 9-12, 9-13, 9-14, 9-15, 9-16, 9-17, 9-18, 9-19, 9-20, 9-21, 9-22, 9-23, 9-24, 9-25, 9-26, 9-27, 9-28, 9-29, 9-30, 9-31, 9-32, 10-26, 10-27, 11-2, 11-37 Histogram 2-8, 2-9, 3-25, 3-26, 7-4, 7-10, 7-11, 7-12, 7-13, 7-14, 7-15, 7-16, 7-17, 7-26, 7-29, 7-34, 8-10, 8-11, 8-14, 8-16, 8-18 Host 1-4, 2-9, 10-7 I Index 1-22, 1-23, 2-3, 2-4, 2-10, 2-11, 2-13, 2-15, 2-16, 2-17, 2-18, 2-20, 2-25, 3-11, 3-16, 3-17, 3-19, 3-21, 3-22, 3-23, 3-28, 3-29, 3-30, 3-32, 3-34, 4-3, 4-4, 4-5, 4-6, 4-7, 4-9, 4-10, 4-11, 4-12, 4-13, 4-14, 4-15, 4-16, 4-17, 4-18, 4-19, 4-20, 4-21, 4-22, 4-23, 4-24, 4-25, 4-26, 4-27, 4-28, 4-29, 4-30, 4-31, 4-32, 4-33, 4-34, 4-35, 4-36, 4-37, 4-38, 4-39, 4-40, 4-41, 4-42, 4-44, 4-45, 4-46, 4-47, 4-48, 4-49, 4-50, 4-51, 4-52, 4-53, 4-54, 4-55, 4-56, 4-57, 4-58, 4-59, 4-60, 4-63, 4-65, 4-67, 4-68, 4-69, 5-25, 5-42, 5-44, 5-45, 5-46, 5-49, 5-50, 6-5, 6-7, 6-8, 6-9, 6-10, 6-11, 6-13, 6-15, 6-16, 6-18, 6-19, 6-20, 6-21, 7-4, 7-6, 7-7, 7-8, 7-9, 7-11, 7-17, 7-19, 7-20, 7-24, 7-26, 7-28, 7-29, 7-30, 7-31, 7-33, 7-34, 8-3, 8-8, 8-10, 8-11, 8-18, 9-3, 9-4, 9-8, 9-9, 9-11, 9-12, 9-13, 9-14, 9-15, 9-16, 9-20, 9-21, 9-22, 9-23, 9-24, 9-25, 9-28, 9-29, 9-30, 10-14, 10-26, 10-27, 10-28, 10-29, 11-5, 11-8, 11-9, 11-10, 11-11, 11-16, 11-17, 11-18, 11-28, 11-33 Index Cluster 4-44, 4-45, 4-46, 7-8, 7-9 Index join 4-4, 4-13, 4-24, 9-13



H

Index Organized Table 4-10, 4-11 Index Scan 4-4, 4-7, 4-13, 4-16, 4-19, 4-20, 4-21, 6-16, 7-6, 9-12, 9-13, 9-14 Index-organized 1-22, 2-20, 4-4, 4-28, 4-29 INDEX_ASC 9-12, 9-14 INDEX_COMBINE 9-12, 9-14, 9-15, 9-16 INDEX_DESC 4-17, 9-12, 9-13, 9-14 INDEX_FFS 4-9, 4-20, 9-12, 9-14 INDEX_JOIN 4-24, 9-13 INDEX_SS 4-23, 9-12, 9-14 Initialization parameter 1-6, 1-18, 2-14, 2-15, 2-24, 2-25, 3-24, 3-25, 3-30, 4-20, 4-37, 4-70, 5-22, 5-35, 6-7, 7-26, 7-31, 7-32, 7-35, 8-11, 8-21, 9-25, 10-5, 10-12, 10-16, 10-30 Inlist Iterator 4-33, 4-50 INSERT 1-8, 3-3, 3-11, 4-39, 5-3, 5-4, 5-7, 5-8, 5-9, 5-10, 5-11, 5-15, 6-14, 7-33, 9-5, 9-6, 9-23, 10-4, 10-19, 10-20, 10-25, 10-26, 10-29, 11-36 INTERSECT 4-48, 4-66, 4-69, 6-11, 9-5, 9-27 Invisible 3-32, 3-34, 4-37, 4-38 IOT 2-20, 4-11, 4-28, 4-29, 4-46 J Java pool 1-6, 1-13, 1-16, 1-18, 3-5 Join 1-14, 1-17, 2-3, 2-4, 2-19, 2-20, 2-21, 3-20, 3-21, 3-24, 3-25, 3-26, 3-28, 3-30, 4-2, 4-3, 4-4, 4-5, 4-8, 4-11, 4-13, 4-24, 4-35, 4-39, 4-45, 4-48, 4-49, 4-51, 4-54, 4-55, 4-56, 4-57, 4-58, 4-59, 4-60, 4-61, 4-62, 4-63, 4-64, 4-65, 4-69, 4-71, 5-3, 5-21, 5-22, 5-24, 5-25, 5-26, 5-32, 5-38, 5-42, 5-43, 5-45, 5-46, 5-47, 5-49, 6-3, 6-4, 6-6, 6-7, 6-8, 6-10, 6-11, 6-12, 6-13, 6-14, 6-15, 6-16, 6-18, 6-19, 6-20, 6-21, 7-3, 7-5, 7-11, 7-16, 7-17, 7-33, 9-2, 9-9, 9-10, 9-12, 9-13, 9-17, 9-20, 9-21, 9-22, 9-24, 9-27, 9-29, 9-30, 11-18 K Key compression 4-10, 4-11



I

Large pool 1-6, 1-12, 1-16, 1-18, 11-22 LEADING 2-3, 4-11, 4-15, 4-19, 4-21, 4-23, 4-36, 6-19, 9-4, 9-20, 9-30 Leaf 4-12, 4-20, 4-21, 4-22, 4-28, 5-14, 5-40, 7-4, 7-6, 7-7, 7-8, 7-24 Library cache 1-9, 1-10, 1-11, 3-5, 3-9, 3-14, 5-4, 5-20, 5-23, 5-24, 8-3, 8-4, 10-16, 10-23, 10-26, 10-28, 10-29 Listener 1-4, 1-5, 10-6 Literal 2-4, 2-5, 2-23, 2-25, 3-29, 8-3, 8-4, 8-7, 8-9, 8-11, 8-12, 8-13, 8-18, 8-19, 9-24 Lock 1-6, 1-7, 1-9, 1-10, 1-21, 1-22, 1-23, 2-9, 2-13, 2-15, 3-12, 3-15, 3-18, 3-21, 3-22, 3-24, 3-27, 3-28, 3-29, 3-30, 3-32, 4-4, 4-5, 4-6, 4-7, 4-8, 4-9, 4-11, 4-12, 4-13, 4-19, 4-20, 4-21, 4-22, 4-28, 4-30, 4-44, 4-45, 4-46, 4-47, 4-49, 4-51, 4-52, 4-56, 4-57, 5-3, 5-12, 5-18, 5-19, 5-48, 7-4, 7-5, 7-6, 7-7, 7-8, 7-9, 7-24, 7-25, 7-28, 7-30, 7-32, 7-33, 7-34, 9-4, 9-5, 9-6, 9-10, 9-17, 9-18, 9-24, 9-26, 9-27, 9-28, 9-29, 10-4, 10-25, 10-29 Locking Statistics 7-34 Lookup table 6-3, 9-24 M Materialized view 2-3, 2-10, 2-19, 9-17, 11-16, 11-17, 11-18 Measures 3-24, 6-3 MERGE 1-14, 3-3, 3-11, 3-21, 3-22, 3-28, 3-30, 3-34, 4-25, 4-34, 4-48, 4-49, 4-51, 4-52, 4-54, 4-58, 4-60, 4-64, 4-65, 4-69, 5-25, 6-8, 6-10, 6-11, 6-13, 6-16, 7-33, 8-14, 8-15, 9-5, 9-6, 9-12, 9-14, 9-16, 9-17, 9-18, 9-21, 9-22, 9-24, 9-26, 9-27, 9-30, 10-13 Min/Max 4-13, 4-53 MINUS 4-32, 4-34, 4-48, 4-66, 4-69, 9-5, 9-27 MMAN 1-15, 1-18, 4-12, 5-4, 5-6, 5-7, 5-8, 5-9, 5-11, 5-12, 5-16, 5-44, 7-22, 8-5, 8-11, 8-12, 10-2, 10-8, 10-10, 10-18, 10-19, 10-23, 10-24, 10-25, 10-26, 10-27, 10-29, 10-30, 11-4, 11-8, 11-16



L

N N-ary 4-3 Nested Loops 3-26, 3-32, 4-47, 4-54, 4-55, 4-56, 4-57, 4-62, 4-63, 4-64, 4-65, 4-67, 5-3, 5-42, 5-43, 5-44, 5-45, 5-46, 7-5, 9-20, 9-21 NO_EXPAND 9-17 NO_FACT 6-17, 9-19 NO_INDEX 9-12, 9-14 NO_MERGE 4-51, 4-52, 9-18 NO_MONITOR 5-35, 9-25 NO_QUERY_TRANSFORMATION 9-17 NO_RESULT_CACHE 4-70, 9-25 NO_USE_HASH 9-22 NO_USE_MERGE 9-22 NO_USE_NL 9-21 NOAPPEND 9-23 NOAUDIT 3-3 Non-equi 4-61, 4-62 NULL 3-13, 4-15, 4-19, 4-20, 4-24, 4-26, 4-27, 4-29, 4-30, 4-39, 4-41, 4-42, 4-63, 4-65, 4-68, 5-11, 5-12, 5-14, 5-25, 5-30, 5-32, 5-44, 7-4, 7-10, 7-17, 7-26, 7-27, 7-30, 7-34, 9-29 O OPEN 1-19, 1-24, 2-14, 2-23, 3-3, 3-6, 3-8, 3-13, 4-63, 10-12, 11-15 OPT_PARAM 9-25



M MMON 1-15, 1-21, 2-3, 2-4, 2-5, 2-6, 2-11, 2-14, 2-15, 2-25, 3-23, 3-24, 4-4, 4-10, 4-15, 4-21, 4-26, 4-44, 4-48, 4-62, 4-63, 7-20, 8-9, 10-4, 10-6, 11-26 Module 2-9, 4-37, 10-4, 10-8, 10-9, 10-10, 10-13, 10-14, 11-4, 11-21 MONITOR 1-3, 1-15, 2-6, 2-7, 2-8, 2-9, 2-10, 2-11, 5-4, 5-15, 5-19, 5-29, 5-35, 5-36, 5-37, 5-38, 5-39, 5-50, 5-52, 7-29, 8-17, 9-25, 10-4, 10-5, 10-8, 10-10, 10-11, 10-12, 10-13, 10-15, 10-29, 11-4, 11-26 Multicolumn Statistics 7-17, 7-18

ORDER BY 4-15, 4-16, 4-17, 4-18, 4-19, 4-46, 4-48, 7-13, 7-15, 9-30, 10-19 ORDERED 3-12, 4-19, 4-20, 4-21, 4-23, 4-46, 4-48, 5-41, 5-47, 7-6, 9-20, 9-21, 9-23, 9-24, 11-21, 11-25 ORDERED_PREDICATES 9-23, 9-24 OS block 1-21 Outer Join 4-61, 4-63 P parallelism 1-3, 4-6, 7-26, 7-29, 7-30 PARALLELIZE 3-6, 3-7, 3-11, 4-40, 7-26 Parent 2-21, 3-20, 4-65, 5-3, 5-10, 5-23, 5-24, 5-40, 5-41, 5-43, 5-45, 5-46, 5-48, 9-5, 11-8 PARSE 1-10, 2-14, 2-23, 2-25, 3-5, 3-6, 3-7, 3-9, 3-13, 3-14, 3-15, 3-18, 5-23, 7-20, 8-4, 8-7, 8-8, 8-13, 8-14, 8-15, 10-16, 10-17, 10-18, 10-23, 10-24, 10-25, 10-26, 10-27, 10-28, 10-29 Partition 1-22, 2-3, 2-10, 2-19, 3-11, 4-3, 4-4, 5-3, 5-12, 6-8, 6-13, 7-26, 7-28, 7-30, 9-12, 9-13, 9-14, 11-16, 11-17, 11-18 Peeking 5-15, 8-2, 8-7, 8-8, 8-13, 8-14, 8-20, 8-21 PGA 1-6, 1-14, 1-15, 1-17, 1-18, 3-5, 3-29, 3-30, 4-49, 5-26, 6-10 PGA_AGGREGATE_TARGET 1-17, 3-29, 3-30, 5-26, 6-10



O optimizer statistics 2-3, 2-11, 2-25, 7-1, 7-2, 7-3, 7-4, 7-25, 7-27, 7-28, 7-29, 7-35, 11-28 OPTIMIZER_CAPTURE_SQL_PLAN_BASELINES 3-32, 3-33, 8-19 OPTIMIZER_DYNAMIC_SAMPLING 3-25, 3-32, 3-33, 7-31, 7-32, 7-33, 9-25 OPTIMIZER_FEATURES_ENABLED 3-32, 3-35 OPTIMIZER_INDEX_CACHING 3-32, 9-25 OPTIMIZER_INDEX_COST_ADJ 3-32, 9-25 OPTIMIZER_MODE 3-32, 3-33, 9-10 OPTIMIZER_USE_INVISIBLE_INDEXES 3-32, 3-34, 4-37, 4-38 OPTIMIZER_USE_PENDING_STATISTICS 3-32, 3-34 OPTIMIZER_USE_SQL_PLAN_BASELINES 3-32, 3-33

PLAN_TABLE 5-4, 5-6, 5-7, 5-10, 5-11, 5-12, 5-13, 5-14, 5-15, 5-20, 5-21, 5-25, 5-32, 5-33, 5-40, 10-20 PLUSTRACE 5-15 Predicate 2-3, 2-25, 3-18, 3-22, 3-25, 3-26, 3-27, 3-34, 4-5, 4-11, 4-14, 4-15, 4-16, 4-17, 4-18, 4-19, 4-20, 4-23, 4-24, 4-25, 4-26, 4-29, 4-30, 4-31, 4-32, 4-33, 4-34, 4-41, 4-49, 4-50, 4-51, 4-52, 4-53, 4-54, 4-55, 4-58, 4-59, 4-60, 4-61, 4-64, 4-67, 4-68, 5-11, 5-12, 5-14, 5-25, 5-42, 5-49, 6-6, 6-10, 6-14, 6-16, 7-3, 7-6, 7-10, 7-14, 7-16, 7-17, 7-18, 7-19, 7-24, 7-31, 7-32, 8-14, 8-15, 8-16, 9-15, 9-21, 9-23, 9-24, 9-26, 11-7, 11-11, 11-18 Preference 7-2, 7-25, 7-26, 7-35 PREPARE 3-3 Primary key 2-20, 3-15, 3-20, 4-11, 4-14, 4-27, 4-28, 4-29, 4-35, 4-40, 5-37, 5-46, 6-3, 6-9, 6-18, 7-7, 8-9 Private SQL area 3-4, 3-8, 3-14 PUSH_PRED 9-24 PUSH_SUBQ 9-24 Q Query block 3-18, 3-21, 3-22, 3-24, 3-28, 4-51, 5-12, 9-4, 9-17, 9-18, 9-26, 9-27, 9-28, 9-29 R Range 3-25, 3-30, 3-32, 4-4, 4-5, 4-6, 4-8, 4-10, 4-13, 4-15, 4-16, 4-17, 4-18, 4-25, 4-26, 4-28, 4-31, 4-34, 4-36, 4-39, 4-49, 4-50, 4-53, 4-56, 4-57, 4-63, 4-65, 4-67, 4-68, 5-29, 5-30, 5-42, 5-44, 5-45, 6-13, 6-16, 7-8, 7-9, 7-10, 7-12, 7-14, 7-26, 8-8, 8-9, 8-10, 8-16, 8-18, 9-8, 9-12, 9-13, 9-14, 9-16, 9-29, 10-26, 10-29, 11-14, 11-18 Redo log buffer 1-6, 1-8, 1-10, 1-11 redo log file 1-8, 1-11, 1-15, 1-19, 2-15 RENAME 3-3, 5-10 Result cache 1-9, 1-15, 3-5, 3-30, 3-31, 4-70, 4-72, 9-25 Result Set 2-5, 4-54, 4-70, 5-44, 5-47, 6-7, 6-9, 6-11, 6-12, 6-14 RESULT_CACHE 3-29, 3-30, 3-31, 4-70, 9-25



P

RESULT_CACHE_MAX_RESULT 3-29, 3-31 RESULT_CACHE_MAX_SIZE 3-29, 3-31 RESULT_CACHE_MODE 3-29, 3-30, 4-70, 9-25 RESULT_CACHE_REMOTE_EXPIRATION 3-29, 3-31 Reverse key 4-10, 4-11 REVOKE 3-3 REWRITE 2-11, 2-27, 3-18, 6-9, 9-17, 11-11, 11-17 ROLLBACK 1-10, 2-13, 3-3, 3-12, 10-16, 10-18 Root 4-12, 4-20, 4-21, 5-40, 7-6, 10-5 Row cache 1-9 ROWID 4-4, 4-6, 4-7, 4-12, 4-13, 4-14, 4-15, 4-16, 4-17, 4-18, 4-19, 4-23, 4-24, 4-25, 4-28, 4-30, 4-31, 4-33, 4-34, 4-36, 4-46, 4-47, 4-49, 4-50, 4-55, 4-56, 4-57, 4-59, 4-63, 4-68, 5-25, 5-42, 5-44, 5-45, 5-46, 6-11, 6-13, 6-15, 6-16, 7-5, 7-8, 9-8, 9-11, 9-16, 10-26, 10-29 ROWID Scan 4-4, 4-7 Rule 2-12, 2-24, 5-41, 5-42, 5-44, 9-6, 11-11, 11-16 S Sample Table Scan 4-4, 4-8, 4-9 SAVEPOINT 3-3, 3-12 Scalability 1-17, 2-12, 2-13 Schema 1-21, 1-22, 2-13, 2-15, 2-18, 2-24, 2-25, 3-3, 3-16, 3-17, 3-24, 5-10, 5-15, 5-20, 6-2, 6-3, 6-4, 6-5, 6-6, 6-22, 7-25, 7-26, 7-27, 7-28, 7-29, 7-30, 7-34, 9-11, 9-21, 10-19, 10-20, 11-12, 11-16, 11-21, 11-38 Segment 1-15, 1-21, 1-22, 1-23, 2-8, 2-15, 3-29, 4-12, 4-20, 4-28, 4-29, 5-27, 5-48, 10-25



R

SELECT 1-4, 2-3, 2-4, 2-5, 2-11, 2-19, 2-20, 3-3, 3-10, 3-11, 3-12, 3-13, 3-16, 3-17, 3-19, 3-20, 3-21, 3-22, 3-23, 3-24, 3-25, 3-26, 3-28, 3-32, 4-3, 4-5, 4-6, 4-7, 4-8, 4-11, 4-14, 4-15, 4-16, 4-17, 4-18, 4-19, 4-20, 4-21, 4-23, 4-24, 4-25, 4-26, 4-27, 4-29, 4-31, 4-32, 4-33, 4-36, 4-38, 4-39, 4-41, 4-47, 4-48, 4-49, 4-50, 4-51, 4-52, 4-53, 4-54, 4-55, 4-56, 4-57, 4-58, 4-59, 4-60, 4-62, 4-63, 4-64, 4-65, 4-67, 4-68, 4-70, 5-3, 5-6, 5-9, 5-10, 5-11, 5-12, 5-14, 5-15, 5-18, 5-25, 5-32, 5-33, 5-34, 5-37, 5-38, 5-42, 5-44, 5-45, 5-47, 5-48, 5-49, 6-5, 6-6, 6-9, 6-12, 6-14, 6-16, 6-18, 6-19, 6-20, 6-21, 7-3, 7-6, 7-8, 7-10, 7-11, 7-13, 7-14, 7-15, 7-16, 7-17, 7-18, 7-19, 7-24, 7-31, 7-32, 7-34, 8-3, 8-4, 8-5, 8-7, 8-8, 8-9, 8-10, 8-12, 8-14, 8-15, 8-16, 8-18, 9-3, 9-5, 9-6, 9-8, 9-10, 9-11, 9-12, 9-13, 9-14, 9-15, 9-16, 9-18, 9-20, 9-21, 9-22, 9-23, 9-24, 9-27, 9-28, 9-29, 9-30, 10-7, 10-12, 10-13, 10-15, 10-17, 10-20, 10-25, 10-28, 10-29, 11-7, 11-8, 11-12, 11-13, 11-14, 11-15, 11-19, 11-20, 11-24, 11-25, 11-33, 11-34, 11-36 Selectivity 2-3, 2-11, 3-24, 3-25, 3-26, 4-3, 4-6, 4-36, 6-14, 7-3, 7-8, 7-10, 7-11, 7-14, 7-16, 7-17, 7-19, 7-24, 7-31, 7-32, 8-8, 8-14, 8-15, 8-16, 8-18, 9-24, 11-7 Semi join 4-61, 4-64 server process 1-4, 1-5, 1-6, 1-7, 1-8, 1-9, 1-10, 1-11, 1-12, 3-11, 3-30, 10-3 Service 1-4, 1-20, 2-8, 2-9, 5-31, 10-3, 10-4, 10-6, 10-7, 10-8, 10-9, 10-10, 10-13, 10-14, 10-31 SERVICE_NAME 10-7, 10-8, 10-14 SERVICE_NAMES 10-8 Session 1-4, 1-5, 1-6, 1-12, 1-13, 1-14, 1-17, 2-8, 2-9, 3-3, 3-30, 3-33, 4-37, 5-20, 5-21, 5-25, 5-27, 5-30, 5-31, 5-35, 5-36, 5-37, 5-38, 5-39, 5-44, 7-33, 8-5, 8-11, 8-12, 9-6, 9-10, 9-27, 10-2, 10-3, 10-4, 10-6, 10-8, 10-10, 10-11, 10-12, 10-13, 10-14, 10-15, 10-17, 10-18, 10-20, 10-30, 11-19, 11-20 SESSION_ID 10-8, 10-11, 10-14 SET ROLE 3-3 SET TRANSACTION 3-3



S

SGA 1-3, 1-4, 1-6, 1-7, 1-8, 1-9, 1-10, 1-11, 1-12, 1-15, 1-16, 1-18, 2-6, 2-8, 3-5, 3-30, 3-31, 4-49, 11-21 SGA_TARGET 1-16 Shared pool 1-6, 1-9, 1-10, 1-11, 1-12, 1-15, 1-16, 1-18, 2-14, 2-22, 2-23, 3-5, 4-70, 5-24 Shared server 1-4, 1-12, 1-14, 6-10, 10-3 Shared SQL area 1-10, 3-4, 3-5, 3-9, 3-14, 3-15, 5-23 Single-table hash cluster 4-46 Skip 4-4, 4-13, 4-21, 4-22, 4-23, 4-36, 4-58, 9-14, 9-17 Small table 4-6, 4-39, 5-49 Snapshot 2-6, 5-27, 5-28, 5-29, 5-30, 5-31, 5-33, 5-34, 11-12, 11-14, 11-32 Snowflake 6-4, 6-21 Soft parse 2-23, 3-14, 8-14, 8-15, 10-23 SORT 1-14, 1-17, 2-5, 2-20, 3-26, 3-27, 3-28, 3-30, 4-11, 4-15, 4-17, 4-19, 4-20, 4-24, 4-27, 4-31, 4-46, 4-48, 4-49, 4-52, 4-53, 4-54, 4-58, 4-60, 4-65, 4-67, 4-69, 5-3, 5-18, 5-19, 5-22, 5-24, 5-25, 5-26, 5-38, 5-47, 6-13, 6-16, 9-3, 9-10, 9-22, 10-18, 10-19, 10-21, 10-22, 10-28, 10-29 Sort area 1-14, 4-49 Sort-merge Join 4-48, 4-54, 4-58, 9-22 Sorted hash cluster 4-46 SPA 1-4, 1-5, 1-8, 1-21, 1-22, 1-23, 1-24, 2-6, 2-8, 2-9, 2-14, 2-15, 2-21, 2-24, 2-25, 3-5, 3-9, 4-5, 4-10, 4-11, 4-35, 4-39, 4-40, 4-46, 4-65, 5-4, 5-5, 5-12, 5-31, 5-34, 5-36, 5-39, 5-48, 6-4, 7-5, 7-14, 7-21, 7-28, 9-3, 9-5, 9-6, 9-23, 10-8, 10-14, 10-16, 10-26, 11-4, 11-8, 11-22, 11-25 SQL Access Advisor 2-10, 5-50, 11-2, 11-10, 11-16, 11-17, 11-18, 11-19, 11-20, 11-21, 11-22, 11-23, 11-24, 11-25, 11-37, 11-38 SQL Management Base 3-33, 5-4, 5-5 SQL monitor 2-10, 5-35, 5-36, 5-37, 5-38, 5-39, 5-50, 5-52, 9-25 SQL profile 2-6, 5-5, 11-5, 11-7, 11-8, 11-9, 11-15, 11-26, 11-27, 11-28, 11-29, 11-30, 11-32, 11-33, 11-36



S

SQL tuning advisor 2-6, 2-10, 2-14, 5-50, 11-2, 11-3, 11-4, 11-5, 11-8, 11-9, 11-12, 11-13, 11-14, 11-15, 11-26, 11-27, 11-28, 11-34, 11-36, 11-37, 11-38 SQL tuning loop 11-9, 11-26 SQL tuning set 2-10, 5-4, 5-6, 11-12, 11-14, 11-17, 11-21, 11-32 Stale 2-3, 3-31, 7-3, 7-5, 7-6, 7-25, 7-26, 7-27, 11-5, 11-6, 11-28, 11-29 Star Join 4-61 star query 6-2, 6-3, 6-5, 6-7, 6-12, 6-14, 6-16, 6-17, 6-22 star schema 6-2, 6-3, 6-4, 6-6, 6-22 Star Transformation 3-18, 4-35, 6-1, 6-2, 6-5, 6-6, 6-7, 6-8, 6-9, 6-12, 6-13, 6-14, 6-15, 6-16, 6-17, 6-22, 6-23, 9-17, 9-19 STAR_TRANSFORMATION 3-29, 3-30, 6-7, 6-17, 9-4, 9-19, 9-25 STAR_TRANSFORMATION_ENABLED 3-29, 3-30, 6-7, 9-25 Statistics 1-16, 1-18, 2-3, 2-6, 2-7, 2-8, 2-9, 2-11, 2-15, 2-25, 3-16, 3-17, 3-18, 3-24, 3-25, 3-26, 3-32, 3-33, 3-34, 4-11, 4-41, 4-42, 5-4, 5-13, 5-15, 5-16, 5-17, 5-18, 5-19, 5-20, 5-22, 5-23, 5-24, 5-26, 5-27, 5-28, 5-29, 5-31, 5-35, 5-37, 5-44, 5-48, 6-7, 7-1, 7-2, 7-3, 7-4, 7-5, 7-6, 7-7, 7-8, 7-9, 7-10, 7-11, 7-12, 7-13, 7-15, 7-17, 7-18, 7-19, 7-20, 7-21, 7-22, 7-23, 7-24, 7-25, 7-26, 7-27, 7-28, 7-29, 7-30, 7-31, 7-34, 7-35, 7-36, 8-10, 8-11, 8-14, 8-15, 8-17, 8-18, 9-3, 9-10, 9-24, 10-2, 10-10, 10-16, 10-17, 10-18, 10-20, 10-23, 10-24, 10-25, 10-26, 10-28, 10-30, 11-5, 11-6, 11-7, 11-8, 11-9, 11-12, 11-14, 11-15, 11-24, 11-26, 11-28, 11-29, 11-32, 11-33 STATISTICS_LEVEL 1-16, 1-18, 5-22, 5-26, 5-35, 5-44, 7-27, 10-16, 11-32 STATS$SQL_PLAN 5-4 Streams pool 1-6, 1-13, 1-16, 1-18, 3-5 Suboptimal 2-3, 2-21, 7-11, 7-19, 8-8, 11-6 Subquery 2-4, 3-11, 3-18, 3-20, 4-61, 4-64, 4-65, 5-42, 6-8, 7-33, 9-5, 9-17, 9-18, 9-24, 9-27 SYSAUX 1-24, 5-5



S

SYSTEM 1-3, 1-4, 1-6, 1-8, 1-11, 1-15, 1-16, 1-17, 1-18, 1-23, 1-24, 2-8, 2-9, 2-11, 2-12, 2-13, 2-14, 2-15, 2-16, 2-22, 2-23, 2-25, 3-3, 3-18, 3-26, 3-30, 3-31, 4-3, 4-8, 4-10, 4-14, 4-15, 4-16, 4-21, 4-22, 4-23, 4-25, 4-29, 4-30, 4-35, 4-37, 4-45, 4-47, 4-49, 4-52, 4-57, 4-59, 4-63, 5-10, 5-17, 5-18, 5-27, 5-28, 5-31, 5-44, 5-46, 5-47, 6-9, 6-14, 7-2, 7-3, 7-4, 7-11, 7-13, 7-15, 7-20, 7-21, 7-22, 7-23, 7-24, 7-26, 7-27, 7-28, 7-29, 7-33, 7-35, 7-36, 8-8, 8-11, 8-12, 8-14, 8-15, 8-19, 9-3, 9-22, 9-24, 9-29, 10-6, 10-8, 10-9, 10-16, 10-20, 11-3, 11-6, 11-8, 11-9, 11-14, 11-17, 11-26, 11-34, 11-36 System statistics 2-11, 7-2, 7-4, 7-20, 7-21, 7-22, 7-23, 7-27, 7-28, 7-35, 7-36, 9-24 T Table 1-9, 1-21, 1-22, 1-23, 1-24, 2-3, 2-5, 2-14, 2-15, 2-16, 2-17, 2-18, 2-19, 2-20, 2-21, 2-25, 3-10, 3-11, 3-12, 3-16, 3-17, 3-18, 3-19, 3-20, 3-21, 3-22, 3-25, 3-26, 3-28, 3-29, 3-30, 3-31, 3-32, 3-33, 3-35, 4-3, 4-4, 4-5, 4-6, 4-7, 4-8, 4-9, 4-10, 4-11, 4-12, 4-13, 4-14, 4-15, 4-16, 4-17, 4-18, 4-19, 4-20, 4-21, 4-23, 4-24, 4-25, 4-26, 4-27, 4-28, 4-29, 4-30, 4-31, 4-32, 4-33, 4-34, 4-35, 4-36, 4-37, 4-39, 4-40, 4-44, 4-45, 4-46, 4-47, 4-49, 4-50, 4-51, 4-52, 4-54, 4-55, 4-56, 4-57, 4-58, 4-59, 4-60, 4-61, 4-62, 4-63, 4-64, 4-65, 4-67, 4-68, 4-70, 5-3, 5-4, 5-5, 5-6, 5-7, 5-8, 5-9, 5-10, 5-11, 5-12, 5-13, 5-14, 5-15, 5-18, 5-20, 5-21, 5-25, 5-31, 5-32, 5-33, 5-34, 5-38, 5-39, 5-40, 5-42, 5-44, 5-45, 5-46, 5-47, 5-48, 5-49, 6-3, 6-4, 6-5, 6-6, 6-7, 6-8, 6-9, 6-10, 6-11, 6-12, 6-13, 6-14, 6-15, 6-16, 6-17, 6-18, 6-20, 6-21, 7-4, 7-5, 7-6, 7-7, 7-8, 7-9, 7-13, 7-15, 7-17, 7-18, 7-19, 7-20, 7-21, 7-22, 7-24, 7-25, 7-26, 7-27, 7-28, 7-29, 7-30, 7-31, 7-32, 7-33, 7-34, 8-4, 8-8, 8-9, 8-10, 8-11, 8-18, 9-3, 9-4, 9-5, 9-6, 9-8, 9-9, 9-10, 9-11, 9-12, 9-13, 9-14, 9-16, 9-19, 9-20, 9-21, 9-22, 9-23, 9-24, 9-26, 9-27, 9-28, 9-29, 9-30, 10-5, 10-17, 10-18, 10-19, 10-20, 10-21, 10-22, 10-25, 10-26, 10-28, 10-29, 11-5, 11-6, 11-8, 11-9, 11-10, 11-17, 11-18, 11-21, 11-25, 11-36



S

Tablespace 1-21, 1-22, 1-23, 1-24, 2-15, 2-25, 4-39, 4-40, 5-5, 5-31, 5-48, 7-21, 11-25 Temporary table 1-21, 1-22, 4-49, 5-7, 5-10, 6-14, 7-31 tkprof 2-8, 5-10, 5-48, 7-35, 10-2, 10-4, 10-13, 10-17, 10-18, 10-19, 10-20, 10-21, 10-22, 10-23, 10-24, 10-25, 10-26, 10-27, 10-28, 10-29, 10-30, 10-31 trace file 1-19, 1-20, 2-6, 2-9, 3-28, 3-37, 5-4, 5-5, 5-14, 5-40, 5-47, 5-48, 7-35, 10-2, 10-3, 10-5, 10-8, 10-10, 10-12, 10-13, 10-14, 10-15, 10-16, 10-17, 10-18, 10-19, 10-20, 10-27, 10-30 Transformer 3-18, 3-19, 3-20, 3-21, 3-22, 3-23 Transitivity 3-18, 3-23 trcsess 2-8, 10-2, 10-4, 10-13, 10-14, 10-15, 10-18, 10-30, 10-31 TRUNCATE 3-3 Tuning mode 11-3 U UGA 4-49 UNION 2-3, 2-4, 2-5, 3-19, 3-22, 4-48, 4-50, 4-66, 4-68, 4-69, 5-48, 9-5, 9-17, 9-27, 9-28, 11-11 UNION ALL 2-3, 2-5, 3-19, 4-50, 4-66, 4-68, 4-69, 5-48, 9-17, 9-27, 11-11 UNIQUE 1-11, 2-5, 2-20, 3-8, 3-20, 4-4, 4-10, 4-11, 4-13, 4-14, 4-15, 4-27, 4-29, 4-39, 4-40, 4-48, 4-50, 4-55, 4-56, 4-60, 4-69, 5-21, 5-24, 5-37, 5-42, 5-44, 5-45, 5-46, 7-7, 7-9, 7-16, 8-11, 9-8, 10-4 Unique 1-11, 2-5, 2-20, 3-8, 3-20, 4-4, 4-10, 4-11, 4-13, 4-14, 4-15, 4-27, 4-29, 4-39, 4-40, 4-48, 4-50, 4-55, 4-56, 4-60, 4-69, 5-21, 5-24, 5-37, 5-42, 5-44, 5-45, 5-46, 7-7, 7-9, 7-16, 8-11, 9-8, 10-4 Unique key 2-20, 3-20, 4-40 UNNEST 3-18, 3-20, 3-34, 4-64, 9-4, 9-17 UPDATE 1-8, 3-3, 3-11, 3-12, 4-7, 4-37, 5-3, 5-15, 5-23, 7-3, 7-20, 7-21, 7-22, 7-33, 9-5, 9-6, 9-8, 9-28, 10-4, 10-25, 10-29 USE_CONCAT 9-17 USE_HASH 5-47, 9-22



T

U USE_MERGE 9-21, 9-22, 9-30 USE_NL 5-45, 9-4, 9-20, 9-21, 9-22, 9-30 USE_NL_WITH_INDEX 9-21 user process 1-3, 1-4, 1-5, 1-11, 1-15, 3-9, 3-14 V$ACTIVE_SESSION_HISTORY 5-31, 5-35, 5-36, 5-38 V$DIAG_INFO 10-5 V$SESSION 5-21, 5-25, 5-35, 5-36, 5-39, 10-8, 10-11, 10-14 V$SESSION_LONGOPS 5-35, 5-36, 5-39 V$SQL 5-4, 5-13, 5-14, 5-20, 5-21, 5-22, 5-23, 5-24, 5-25, 5-26, 5-32, 5-35, 5-36, 5-37, 5-38, 5-40, 5-44, 5-48, 8-3, 8-14, 8-16, 8-17, 11-17 V$SQL_CS_HISTOGRAM 8-16 V$SQL_CS_SELECTIVITY 8-16 V$SQL_CS_STATISTICS 8-17 V$SQL_MONITOR 5-4, 5-35, 5-36, 5-37 V$SQL_PLAN 5-4, 5-13, 5-14, 5-20, 5-21, 5-22, 5-23, 5-24, 5-25, 5-26, 5-35, 5-36, 5-38, 5-40, 5-44, 5-48 V$SQL_PLAN_MONITOR 5-4, 5-35, 5-36, 5-38 V$SQL_PLAN_STATISTICS 5-13, 5-20, 5-22, 5-23, 5-24, 5-48 V$SQL_PLAN_STATISTICS_ALL 5-13, 5-20, 5-22, 5-23, 5-24 V$SQL_WORKAREA 5-20, 5-22, 5-23, 5-24 V$SQLAREA 5-21, 5-23, 5-24, 5-25 View 1-2, 1-3, 1-6, 1-20, 1-22, 1-26, 2-3, 2-6, 2-8, 2-9, 2-10, 2-11, 2-16, 2-19, 2-21, 2-25, 2-27, 3-6, 3-14, 3-15, 3-18, 3-21, 3-22, 3-25, 3-26, 3-32, 3-34, 3-37, 4-8, 4-10, 4-24, 4-35, 4-37, 4-38, 4-43, 4-50, 4-51, 4-52, 4-54, 4-72, 5-4, 5-6, 5-13, 5-15, 5-20, 5-21, 5-22, 5-23, 5-24, 5-27, 5-29, 5-30, 5-31, 5-32, 5-35, 5-36, 5-38, 5-39, 5-49, 5-52, 6-6, 6-8, 6-15, 6-18, 6-23, 7-4, 7-9, 7-11, 7-13, 7-15, 7-17, 7-18, 7-19, 7-25, 7-26, 7-28, 7-31, 7-33, 7-34, 7-35, 7-36, 8-13, 8-14, 8-16, 8-17, 8-21, 9-3, 9-4, 9-17, 9-18, 9-24, 9-25, 9-26, 9-27, 9-28, 9-29, 9-31, 9-32, 10-6, 10-9, 10-12, 10-14, 10-18, 10-30, 10-31, 11-5, 11-8, 11-15, 11-16, 11-17, 11-18, 11-19, 11-20, 11-23, 11-24, 11-25, 11-28, 11-33, 11-34, 11-38



V

V View merging 3-18, 3-21, 3-34, 9-17, 9-18


W Wait 2-8, 2-9, 2-12, 2-15, 5-33, 5-35, 5-37, 5-38, 10-10, 10-11, 10-12, 10-15, 10-16, 10-17, 10-19, 11-36 WHENEVER 3-3, 4-62, 7-3, 7-25


11g SQL Tuning Workshop - Volume 2

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